A Systematic Survey of Industrial Internet of Things Security: Requirements and Fog Computing Opportunities
Open accessAbstract
A key application of the Internet of Things (IoT) paradigm lies within industrial contexts. Indeed, the emerging Industrial Internet of Things (IIoT), commonly referred to as Industry 4.0, promises to revolutionize production and manufacturing through the use of large numbers of networked embedded sensing devices, and the combination of emerging computing technologies, such as Fog/Cloud Computing and Artificial Intelligence. The IIoT is characterized by an increased degree of inter-connectivity, which not only creates opportunities for the industries that adopt it, but also for cyber-criminals. Indeed, IoT security currently represents one of the major obstacles that prevent the widespread adoption of IIoT technology. Unsurprisingly, such concerns led to an exponential growth of published research over the last few years. To get an overview of the field, we deem it important to systematically survey the academic literature so far, and distill from it various security requirements as well as their popularity. This paper consists of two contributions: our primary contribution is a systematic review of the literature over the period 2011-2019 on IIoT Security, focusing in particular on the security requirements of the IIoT. Our secondary contribution is a reflection on how the relatively new paradigm of Fog computing can be leveraged to address these requirements, and thus improve the security of the IIoT.
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Cites
Fog computing and its role in the internet of things
Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012) · Proceedings of the first edition of the MCC workshop on Mobile cloud computing · doi:10.1145/2342509.2342513 · Cited by 6,244 · see citing works
Guidelines for conducting systematic mapping studies in software engineering: An update
Petersen, K., Vakkalanka, S., & Kuzniarz, L. (2015) · Information and Software Technology · doi:10.1016/j.infsof.2015.03.007 · Cited by 2,669 · cited 2× · see citing works
“[20] and utilize the suggested template for describing our approach.”
MethodIndustrial Internet of Things: Challenges, Opportunities, and Directions
Sisinni, E., Saifullah, A., Han, S., Jennehag, U., & Gidlund, M. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2852491 · Cited by 2,380 · cited 3× · see citing works
“Within the context provided by IoT and IIoT applications, this brings some extra challenges [15], [17], [49].”
BackgroundStuxnet: Dissecting a cyberwarfare weapon
Langner, R. (2011) · IEEE Security & Privacy Magazine · doi:10.1109/msp.2011.67 · Cited by 1,922 · cited 2× · see citing works
“In fact, traditional industrial environments have been subject to attacks in the past, sometimes with devastating results (e.g., StuxNet [5] or CrashOverride/Industroyer [6]).”
The Internet of Things—A survey of topics and trends
Whitmore, A., Agarwal, A., & Da Xu, L. (2015) · Information Systems Frontiers · doi:10.1007/s10796-014-9489-2 · Cited by 1,568 · cited 1× · see citing works
“1) Key Distribution: Key distribution is a challenging requirement for many applications in the IoT [68], and naturally extends to the IIoT.”
BackgroundThe industrial internet of things (IIoT): An analysis framework
Boyes, H. A., Hallaq, B., Cunningham, J., & Watson, T. (2018) · Computers in Industry · doi:10.1016/j.compind.2018.04.015 · Cited by 1,496 · cited 1× · see citing works
“[232].”
All one needs to know about fog computing and related edge computing paradigms: A complete survey
Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., & Jue, J. P. (2019) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2019.02.009 · Cited by 1,368 · see citing works
A survey on LPWA technology: LoRa and NB-IoT
Sinha, R. S., Wei, Y., & Hwang, S.-H. (2017) · ICT Express · doi:10.1016/j.icte.2017.03.004 · Cited by 1,020 · cited 1× · see citing works
“are LPWAN technologies [229].”
Security and privacy challenges in industrial internet of things
Sadeghi, A., Wachsmann, C., & Waidner, M. (2015) · Proceedings - ACM IEEE Design Automation Conference · doi:10.1145/2744769.2747942 · Cited by 920 · cited 6× · see citing works
“At the same time, remote attestation methods implemented purely in software typically have to rely on very strong assumptions that are hard to achieve in practice [17].”
BackgroundMethodInfluentialCyber physical systems in the context of Industry 4.0
Jazdi, N. (2014) · IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) · doi:10.1109/aqtr.2014.6857843 · Cited by 847 · see citing works
Neshenko, N., Bou‐Harb, E., Crichigno, J., Kaddoum, G., & Ghani, N. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2910750 · Cited by 832 · see citing works
MQTT-S — A publish/subscribe protocol for Wireless Sensor Networks
Hunkeler, U., Truong, H. L., & Stanford-Clark, A. (2008) · 2008 3rd International Conference on Communication Systems Software and Middleware and Workshops (COMSWARE '08) · doi:10.1109/comswa.2008.4554519 · Cited by 813 · cited 1× · see citing works
“basic and insecure authentication methods [57].”
IoT: Internet of Threats? A Survey of Practical Security Vulnerabilities in Real IoT Devices
Meneghello, F., Calore, M., Zucchetto, D., Polese, M., & Zanella, A. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2935189 · Cited by 812 · cited 1× · see citing works
“In [11], the authors survey the literature for real IoT attacks and present a taxonomy.”
BackgroundMahnke, W., Leitner, S.-H., & Damm, M. (2009) · Springer eBooks · doi:10.1007/978-3-540-68899-0 · Cited by 722 · see citing works
Internet of things security: A top-down survey
Kouicem, D. E., Bouabdallah, A., & Lakhlef, H. (2018) · Computer Networks · doi:10.1016/j.comnet.2018.03.012 · Cited by 586 · cited 1× · see citing works
“In [13], the authors provide a top-down survey of IoT security.”
BackgroundDeploying Fog Computing in Industrial Internet of Things and Industry 4.0
Aazam, M., Zeadally, S., & Harras, K. A. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2855198 · Cited by 572 · cited 1× · see citing works
“This is also discussed in [258], where a number of Fog use-cases and research challenges are listed.”
BackgroundTowards secure industrial IoT: blockchain system with credit-based consensus mechanism
Huang, J., Kong, L., Chen, G., Wu, M.-Y., Liu, X., & Zeng, P. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2903342 · Cited by 563 · cited 1× · see citing works
“[151] list three main challenges in blockchain technology: the trade-off between efficiency and security, coexistence of transparency and privacy, and conflicts between concurrency and throughput.”
BackgroundMachine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things
Zolanvari, M., Teixeira, M. A., Gupta, L., Khan, K. M., & Jain, R. K. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2912022 · Cited by 526 · cited 1× · see citing works
“For a more thorough overview of the state machine learning for industrial IDSs, we refer the interested reader to [207].”
BackgroundNarrow Band Internet of Things
Chen, M., Miao, Y., Hao, Y., & Hwang, K. (2017) · IEEE Access · doi:10.1109/access.2017.2751586 · Cited by 459 · cited 1× · see citing works
“[223] list a number of security requirements in a review of the Narrow Band IoT (NB-IoT) standard.”
BackgroundLi, X., Niu, J., Bhuiyan, M. Z. A., Wu, F., Karuppiah, M., & Kumari, S. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2773666 · Cited by 415 · cited 1× · see citing works
“require biometric features ([72], [77]), smart cards ([72]) or NFC tags ([36], [37], [67], [225]), in the authentication pro-”
BackgroundLin, C., He, D., Huang, X., Choo, K. R., & Vasilakos, A. V. (2018) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2018.05.005 · Cited by 404 · see citing works
Cybersecurity for Industry 4.0 in the current literature: A reference framework
Lezzi, M., Lazoi, M., & Corallo, A. (2018) · Computers in Industry · doi:10.1016/j.compind.2018.09.004 · Cited by 404 · cited 1× · see citing works
“To the best of our knowledge, the most recent works focused on reviewing IIoT security are [14] and [15].”
BackgroundSajid, A., Abbas, H., & Saleem, K. (2016) · IEEE Access · doi:10.1109/access.2016.2549047 · Cited by 401 · cited 1× · see citing works
“Some older surveys dated back to 2015 and 2016 mention IIoT security requirements [17], [18], but they also refrain from an in-depth discussion.”
BackgroundFoundations and Evolution of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog
Donno, M. D., Tange, K., & Dragoni, N. (2019) · IEEE Access · doi:10.1109/access.2019.2947652 · Cited by 372 · cited 2× · see citing works
“To maintain consistency with earlier work, we use the definition of Fog computing as used in [254]; a paradigm that extends the Cloud and integrates Edge and IoT, while providing a new, horizontally scalable highly virtualized layer that distributes computing, storage, control, and networking capabilities across the C…”
BackgroundMethodSelf-citationBlockchain-Enabled Data Collection and Sharing for Industrial IoT With Deep Reinforcement Learning
Liu, C. H., Lin, Q., & Wen, S. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2890203 · Cited by 342 · cited 1× · see citing works
“Other blockchain-based proposals in this domain are [153] and [154].”
BackgroundA Lightweight Authentication Mechanism for M2M Communications in Industrial IoT Environment
Esfahani, A., Μαντάς, Γ., Matischek, R., Saghezchi, F. B., Rodrı́guez, J., Bicaku, A., Maksuti, S., Tauber, M., Schmittner, C., & Bastos, J. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2737630 · Cited by 340 · see citing works
Yin, C., Xi, J., Sun, R., & Wang, J. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2773646 · Cited by 334 · see citing works
Authentication Protocols for Internet of Things: A Comprehensive Survey
Ferrag, M. A., Maglaras, L. A., Janicke, H., Jiang, J., & Shu, L. (2017) · Security and Communication Networks · doi:10.1155/2017/6562953 · Cited by 331 · cited 1× · see citing works
“Authentication of remote entities (both humans and machines, or even applications) is a key concern for many forms of IoT communication [31].”
BackgroundFernandez-Carames, T. M., & Fraga-Lamas, P. (2019) · IEEE Access · doi:10.1109/access.2019.2908780 · Cited by 321 · cited 1× · see citing works
“The aforementioned concerns are also identified in [148], where the authors further state that while blockchain promises enhanced data security and availability, for the IIoT domain there remain challenges regarding data privacy, integrity, and identify certification.”
BackgroundHandling a trillion (unfixable) flaws on a billion devices
Yu, T., Sekar, V., Seshan, S., Agarwal, Y., & Xu, C. (2015) · ACM Workshop on Hot Topics in Networks (HotNets) · doi:10.1145/2834050.2834095 · Cited by 313 · see citing works
Fu, J.-S., Liu, Y., Chao, H., Bhargava, B., & Zhang, Z. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2793350 · Cited by 281 · cited 2× · see citing works
“[149] propose one way of ensuring confidentiality”
MethodAnalyzing Adversarial Attacks against Deep Learning for Intrusion Detection in IoT Networks
Ibitoye, O., Shafiq, O., & Matrawy, A. (2019) · 2019 IEEE Global Communications Conference (GLOBECOM) · doi:10.1109/globecom38437.2019.9014337 · Cited by 281 · cited 1× · see citing works
“In [186], the authors show that one can reliably create adversarial samples that defeat deep learning based systems.”
BackgroundLaaki, H., Miché, Y., & Tammi, K. (2019) · IEEE Access · doi:10.1109/access.2019.2897018 · Cited by 273 · cited 1× · see citing works
“[96] also identify the possibility for hardware attestation to protect the digital”
Background6TiSCH: deterministic IP-enabled industrial internet (of things)
Dujovne, D., Watteyne, T., Vilajosana, X., & Thubert, P. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6979984 · Cited by 268 · cited 1× · see citing works
“6TiSCH [228] is a standardization effort by the Internet Engineering Task Force (IETF), aimed at low-power determin-”
MethodContext-Sensitive Access in Industrial Internet of Things (IIoT) Healthcare Applications
Al-Turjman, F. M., & Alturjman, S. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2808190 · Cited by 265 · cited 1× · see citing works
“The Fifth generation cellular network technology (5G) authentication scheme for smart devices proposed in [70] uses Cloud-based learning to dynamically identify and authenticate users based on behavioral patterns, showing another approach for minimizing user interaction.”
BackgroundAdaptive Intrusion Detection of Malicious Unmanned Air Vehicles Using Behavior Rule Specifications
Mitchell, R., & Chen, I.-R. (2013) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2013.2265083 · Cited by 247 · see citing works
A Secure FaBric Blockchain-Based Data Transmission Technique for Industrial Internet-of-Things
Liang, W., Tang, M., Long, J., Peng, X., Xu, J., & Li, K. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2907092 · Cited by 242 · cited 1× · see citing works
“Other blockchain-based proposals in this domain are [153] and [154].”
BackgroundCertificateless Searchable Public Key Encryption Scheme for Industrial Internet of Things
Ma, M., He, D., Kumar, N., Choo, K. R., & Chen, J. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2703922 · Cited by 241 · see citing works
Das, A. K., Wazid, M., Kumar, N., Vasilakos, A. V., & Rodrigues, J. J. P. C. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2877690 · Cited by 234 · cited 3× · see citing works
“require biometric features ([72], [77]), smart cards ([72]) or NFC tags ([36], [37], [67], [225]), in the authentication pro-”
BackgroundAn Authentic-Based Privacy Preservation Protocol for Smart e-Healthcare Systems in IoT
Deebak, B. D., Al‐Turjman, F., Aloqaily, M., & Alfandi, O. (2019) · IEEE Access · doi:10.1109/access.2019.2941575 · Cited by 213 · cited 1× · see citing works
“[73] combine smart cards, passwords, and biometrics.”
A Robust and Energy Efficient Authentication Protocol for Industrial Internet of Things
Li, X., Peng, J., Niu, J., Wu, F., Liao, J., & Choo, K. R. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2787800 · Cited by 212 · see citing works
Provably Secure and Lightweight Certificateless Signature Scheme for IIoT Environments
Karati, A., Islam, S. H., & Karuppiah, M. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2794991 · Cited by 209 · see citing works
Network and information security challenges within Industry 4.0 paradigm
Pereira, T., Barreto, L., & Amaral, A. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.09.047 · Cited by 200 · cited 1× · see citing works
“Within the context provided by IoT and IIoT applications, this brings some extra challenges [15], [17], [49].”
BackgroundA Multi-Level DDoS Mitigation Framework for the Industrial Internet of Things
Yan, Q., Huang, W., Luo, X., Gong, Q., & Yu, F. R. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700621 · Cited by 189 · cited 2× · see citing works
“A second reason can be found in providing protection against Denial of Service (DoS) attacks [115] and improving congestion control”
Background6LoWPAN Compressed DTLS for CoAP
Raza, S., Trabalza, D., & Voigt, T. (2012) · IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS) · doi:10.1109/dcoss.2012.55 · Cited by 174 · cited 3× · see citing works
“For example, the authors state that support for Datagram Transport Layer Security (DTLS) and TLS is taken into consideration.”
MethodInfluentialThreat-Based Security Analysis for the Internet of Things
Atamli, A. W., & Martin, A. (2014) · 2014 International Workshop on Secure Internet of Things · doi:10.1109/siot.2014.10 · Cited by 169 · cited 1× · see citing works
“Indeed, [15] and [118] identify resilience as an important security challenge for the IIoT.”
BackgroundWang, D., & Wang, P. (2014) · Ad Hoc Networks · doi:10.1016/j.adhoc.2014.03.003 · Cited by 162 · see citing works
DDoS-Capable IoT Malwares: Comparative Analysis and Mirai Investigation
Donno, M. D., Dragoni, N., Giaretta, A., & Spognardi, A. (2018) · Security and Communication Networks · doi:10.1155/2018/7178164 · Cited by 157 · see citing works
Self-citationZhang, Y., Deng, R. H., Zheng, D., Li, J., Wu, P., & Cao, J. P. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2894108 · Cited by 154 · see citing works
A New Threat Intelligence Scheme for Safeguarding Industry 4.0 Systems
Moustafa, N., Adi, E., Turnbull, B., & Hu, J. (2018) · IEEE Access · doi:10.1109/access.2018.2844794 · Cited by 153 · cited 2× · see citing works
“to monitor infrastructure, and respond to known and unknown threats when necessary [55], [193], [198], [206].”
BackgroundZhang, X., Xu, C., Wang, H., Zhang, Y., & Wang, S. (2019) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2019.2914117 · Cited by 146 · cited 1× · see citing works
“Seeking to remedy this, there has been a recent increase in research efforts in modern cryptographic techniques such as homomorphic encryption, allowing for computation on encrypted data ([65], [66]), and searchable encryption, enabling search operations on encrypted data ([146], [161]).”
BackgroundUsing Smart Edge IoT Devices for Safer, Rapid Response With Industry IoT Control Operations
Condry, M. W., & Nelson, C. B. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2513672 · Cited by 145 · cited 1× · see citing works
“This is also necessary for the model described by Condry and Nielson [26].”
MethodIIoT cybersecurity risk modeling for SCADA systems
Falco, G., Caldera, C., & Shrobe, H. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2822842 · Cited by 137 · cited 1× · see citing works
“separation has been identified as one of the most severe shortcomings in existing systems, such as the Supervisory Control And Data Acquisition (SCADA) protocol [100].”
MethodApplying Blockchain in Industry 4.0 Applications
Mohamed, N., & Al‐Jaroodi, J. (2019) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc.2019.8666558 · Cited by 130 · see citing works
Google Scholar’s Ranking Algorithm : An Introductory OverviewPreprint
Beel, J., & Gipp, B. (2009) · Cited by 126 · see citing works
Cloud Manufacturing: Security, Privacy, and Forensic Concerns
Esposito, C., Castiglione, A., Martini, B., & Choo, K. R. (2016) · IEEE Cloud Computing · doi:10.1109/mcc.2016.79 · Cited by 122 · cited 1× · see citing works
“[29].”
Building Redactable Consortium Blockchain for Industrial Internet-of-Things
Huang, K., Zhang, X., Mu, Y., Wang, X., Yang, G., Du, X., Rezaeibagha, F., Xia, Q., & Guizani, M. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2901011 · Cited by 118 · cited 1× · see citing works
“This comes at the cost of some security [64], but further research is needed.”
BackgroundToward Secure and Provable Authentication for Internet of Things: Realizing Industry 4.0
Garg, S., Kaur, K., Kaddoum, G., & Choo, K. R. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2942271 · Cited by 113 · cited 1× · see citing works
“Some recent work that aims to facilitate this is done in [74], and uses trusted components such as Physically Uncloneable Functions (PUFs).”
BackgroundHybrid intrusion detection system for edge-based IIoT relying on machine-learning-aided detection
Yao, H., Gao, P., Zhang, P., Wang, J., Jiang, C., & Lu, L. (2019) · IEEE Network · doi:10.1109/mnet.001.1800479 · Cited by 113 · see citing works
Yu, X., & Guo, H. (2019) · IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS) · doi:10.1109/vts-apwcs.2019.8851679 · Cited by 105 · cited 2× · see citing works
“This is echoed by Yu and Guo [10], who, in a short survey on the differences between IIoT and IoT security, find that for the”
BackgroundGeorge, G., & Thampi, S. M. (2018) · IEEE Access · doi:10.1109/access.2018.2863244 · Cited by 104 · cited 1× · see citing works
“In [110], George and Thampi state that the availability of security updates is a critical concern for IIoT devices, but that due to some IIoT systems being so lightweight and the infrastructure not being fixed, it is extremely difficult to always patch all devices in a network.”
BackgroundFlatt, H., Schriegel, S., Jasperneite, J., Trsek, H., & Adamczyk, H. (2016) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2016.7733634 · Cited by 101 · see citing works
RERUM: Building a reliable IoT upon privacy- and security- enabled smart objects
Pöhls, H. C., Angelakis, V., Suppan, S., Fischer, K., Oikonomou, G., Τράγος, Η., Rodriguez, R. D., & Mouroutis, T. (2014) · IEEE Wireless Communications and Networking Conference Workshops (WCNCW) · doi:10.1109/wcncw.2014.6934872 · Cited by 100 · see citing works
Distributed Access Control with Privacy Support in Wireless Sensor Networks
He, D., Bu, J., Zhu, S., Chan, S., & Chen, C. (2011) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2011.072511.102283 · Cited by 96 · cited 1× · see citing works
“[102].”
A fog computing based approach to DDoS mitigation in IIoT systems
Zhou, L., Guo, H., & Deng, G. (2019) · Computers & Security · doi:10.1016/j.cose.2019.04.017 · Cited by 95 · cited 1× · see citing works
“[205], where local virtual network functions, Fog,”
Securing RPL routing protocol from blackhole attacks using a trust-based mechanism
Airehrour, D., Gutiérrez, J., & Ray, S. K. (2016) · International Telecommunication Networks and Applications Conference (ITNAC) · doi:10.1109/atnac.2016.7878793 · Cited by 92 · cited 1× · see citing works
“[59] argue that traditional Public Key”
Lightweight Searchable Public-Key Encryption for Cloud-Assisted Wireless Sensor Networks
Xu, P., He, S., Wang, W., Susilo, W., & Jin, H. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2784395 · Cited by 92 · cited 2× · see citing works
“[159] propose a similar solution, also relying on trapdoors to perform search queries on encrypted data sets in the Cloud.”
MethodTowards secure and efficient energy trading in IIoT-enabled energy internet: A blockchain approach
Guan, Z., Lu, X. Y., Wang, N., Wu, J., Du, X., & Guizani, M. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.09.027 · Cited by 92 · see citing works
CyberFactory#1 — Securing the industry 4.0 with cyber-ranges and digital twins
Bécue, A., Fourastier, Y., Praça, I., Alexandre, S., Baron, C., Gradussofs, B., Pouille, E., & Thomas, C. (2018) · IEEE International Workshop on Factory Communication Systems (WFCS) · doi:10.1109/wfcs.2018.8402377 · Cited by 89 · cited 1× · see citing works
“[23] state that it is necessary to improve the prevention, detection, investigation, and response to adversarial machine learning attempts on AI-powered modules.”
BackgroundDesign patterns for the industrial Internet of Things
Bloom, G., Alsulami, B., Nwafor, E., & Bertolotti, I. C. (2018) · 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS) · doi:10.1109/wfcs.2018.8402353 · Cited by 89 · cited 1× · see citing works
“[163] investigated input-output patterns in existing IIoT applications in order to gain a better understanding”
A Unified Trustworthy Environment Establishment Based on Edge Computing in Industrial IoT
Wang, T., Wang, P., Cai, S., Ma, Y., Liu, A., & Xie, M. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2955152 · Cited by 88 · see citing works
Sharpe, R. G., van Lopik, K., Neal, A. D., Goodall, P. A., CONWAY, P. P., & West, A. A. (2019) · Computers in Industry · doi:10.1016/j.compind.2019.02.007 · Cited by 87 · see citing works
Access Control Policy Enforcement for Zero-Trust-Networking
Vanickis, R., Jacob, P., Dehghanzadeh, S., & Lee, B. (2018) · 2018 29th Irish Signals and Systems Conference (ISSC) · doi:10.1109/issc.2018.8585365 · Cited by 86 · cited 1× · see citing works
“[108] make the observation that due to the increase in frequency and sophistication of security attacks in recent years, there is a need to include risk assessment in the”
BackgroundDelsing, J. (2017) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2017.2759342 · Cited by 84 · see citing works
Secure Online/Offline Data Sharing Framework for Cloud-Assisted Industrial Internet of Things
Miao, Y., Tong, Q., Choo, K. R., Liu, X., Deng, R. H., & Li, H. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2923068 · Cited by 83 · cited 1× · see citing works
“[155] also propose a Cloud-assisted method in the context of an e-health scenario, while attempting to minimize intensive tasks such as decryption and decryption at the Edge”
MethodApplicability of the IEC 62443 standard in Industry 4.0 / IIoT
Leander, B., Čaušević, A., & Hansson, H. (2019) · Proceedings of the 14th International Conference on Availability, Reliability and Security · doi:10.1145/3339252.3341481 · Cited by 82 · cited 1× · see citing works
“[127] investigate the applicability”
Faster Authenticated Key Agreement With Perfect Forward Secrecy for Industrial Internet-of-Things
Yang, Z., He, J., Tian, Y., & Zhou, J. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2963328 · Cited by 82 · see citing works
New Security Mechanisms of High-Reliability IoT Communication Based on Radio Frequency Fingerprint
Tian, Q., Lin, Y., Guo, X., Wen, J., Fang, Y., Rodrı́guez, J., & Mumtaz, S. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2913627 · Cited by 80 · see citing works
Self-Sovereign Identity: Use-cases, Technologies, and Challenges for Industrial IoT
Bartolomeu, P. C., Vieira, E., Hosseini, S. M., & Ferreira, J. (2019) · 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2019.8869262 · Cited by 79 · see citing works
Lightweight & secure industrial IoT communications via the MQ telemetry transport protocol
Katsikeas, S., Fysarakis, K., Miaoudakis, A., Bemten, A. V., Askoxylakis, I. G., Papaefstathiou, I., & Plemenos, A. (2017) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc.2017.8024687 · Cited by 78 · cited 3× · see citing works
“encryption support [34], [143], and hardware acceleration for the cryptographic primitives used in these is starting to appear in lightweight products [251].”
BackgroundMethodZhang, Y., Huang, H. M., Yang, L., Xiang, Y., & Li, M. (2019) · IEEE Network · doi:10.1109/mnet.001.1800478 · Cited by 78 · see citing works
Internet of Things for Smart Manufacturing System: Trust Issues in Resource Allocation
Jeong, S., Na, W., Kim, J., & Cho, S. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2814063 · Cited by 77 · see citing works
Effect of Imbalanced Datasets on Security of Industrial IoT Using Machine Learning
Zolanvari, M., Teixeira, M. A., & Jain, R. K. (2018) · IEEE International Conference on Intelligence and Security Informatics (ISI) · doi:10.1109/isi.2018.8587389 · Cited by 77 · cited 2× · see citing works
“Due to the sheer amount of data generated by IIoT devices and the low attack frequency, obtained data sets that can be used for machine learning approaches to intrusion detection tend to be very imbalanced [206].”
BackgroundBabiceanu, R. F., & Seker, R. (2018) · Computers in Industry · doi:10.1016/j.compind.2018.10.004 · Cited by 75 · see citing works
A Security Analysis Method for Industrial Internet of Things
Mouratidis, H., & Diamantopoulou, V. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2832853 · Cited by 74 · cited 1× · see citing works
“Mouratidis and Diamantopoulu [43] take things even further by proposing a more formal security analysis method for the IIoT.”
MethodHan, G., Wang, H., Xu, M., Liu, L., Jiang, J., & Peng, Y. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2953937 · Cited by 73 · cited 1× · see citing works
“should be deployed such as the one proposed in [167].”
BackgroundTowards effective security control assignment in the Industrial Internet of Things
Hassanzadeh, A., Modi, S. K., & Mulchandani, S. (2015) · IEEE World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2015.7389155 · Cited by 72 · cited 3× · see citing works
“Another security-by-design approach recommends the usage of security control assignment matrices to determine the types of security controls that should be present in various parts of a system [132].”
BackgroundLightweight Searchable Public-Key Encryption with Forward Privacy over IIoT Outsourced Data
Chen, B., Wu, L., Kumar, N., Choo, K. R., & He, D. (2019) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2019.2921113 · Cited by 71 · see citing works
Security trends and advances in manufacturing systems in the era of industry 4.0
Chhetri, S. R., Rashid, N., Faezi, S., & Faruque, M. A. A. (2017) · International Conference on Computer Aided Design · doi:10.1109/iccad.2017.8203896 · Cited by 70 · cited 1× · see citing works
“described by [130] below: • Confidentiality pertains to protecting information in all its forms.”
BackgroundTrustworthy Industrial IoT Gateways for Interoperability Platforms and Ecosystems
Fraile, F., Tagawa, T., Poler, R., & Ortíz, Á. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2832041 · Cited by 69 · cited 2× · see citing works
“[84] provide some concrete examples showing why non-repudiation can be considered a security requirement.”
BackgroundA review on the readiness level and cyber-security challenges in Industry 4.0
Benias, N., & Markopoulos, A. P. (2017) · doi:10.23919/seeda-cecnsm.2017.8088234 · Cited by 66 · cited 1× · see citing works
“Traditionally however, availability and integrity are considered more favorable than confidentiality for industrial environments [129], [132], as they have a measurable economic impact.”
BackgroundIndustrial IoT security threats and concerns by considering Cisco and Microsoft IoT reference models
Bakhshi, Z., Balador, A., & Mustafa, J. (2018) · IEEE Wireless Communications and Networking Conference Workshops (WCNCW) · doi:10.1109/wcncw.2018.8368997 · Cited by 66 · cited 2× · see citing works
“the recent popularity of Cloud storage services, these issues require careful consideration [98].”
BackgroundMethodA System Architecture for Software-Defined Industrial Internet of Things
Hu, P. (2015) · IEEE International Conference on Ubiquitous Wireless Broadband · doi:10.1109/icuwb.2015.7324414 · Cited by 65 · see citing works
Hardware-security technologies for industrial IoT: TrustZone and security controller
Lesjak, C., Hein, D. M., & Winter, J. (2015) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2015.7392493 · Cited by 65 · see citing works
Zhou, L. Q., Yeh, K., Hancke, G. P., Liu, Z., & Su, C. (2018) · IEEE Signal Processing Magazine · doi:10.1109/msp.2018.2846297 · Cited by 65 · cited 1× · see citing works
“to monitor infrastructure, and respond to known and unknown threats when necessary [55], [193], [198], [206].”
BackgroundChallenges and Research Issues of Data Management in IoT for Large-Scale Petrochemical Plants
Shu, L., Mukherjee, M., PECHT, M. G., Crespi, N., & Han, S. N. (2017) · IEEE Systems Journal · doi:10.1109/jsyst.2017.2700268 · Cited by 64 · see citing works
Behavior and Vulnerability Assessment of Drones-Enabled Industrial Internet of Things (IIoT)
Sharma, V., Choudhary, G., Ko, Y., & You, I. (2018) · IEEE Access · doi:10.1109/access.2018.2856368 · Cited by 64 · cited 2× · see citing works
“[199] identify a number of security requirements that are specific to this scenario, as well as several requirements that are more generally applicable.”
BackgroundCui, H., Deng, R. H., Liu, J. K., Yi, X., & Li, Y. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2813304 · Cited by 63 · see citing works
Network Slicing for Critical Communications in Shared 5G Infrastructures - An Empirical Evaluation
Kurtz, F., Bektas, C., Dorsch, N., & Wietfeld, C. (2018) · IEEE International Conference on Network Softwarization (NetSoft) · doi:10.1109/netsoft.2018.8460110 · Cited by 62 · cited 1× · see citing works
“[224]”
Hussain, S., & Chaudhry, S. A. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2934947 · Cited by 62 · cited 1× · see citing works
“is proposed, combining smart cards and biometrics, although recent work shows that their protocol is not secure against various attacks [75].”
BackgroundFog Computing as Enabler for Blockchain-Based IIoT App Marketplaces - A Case Study
Seitz, A., Henze, D., Miehle, D., Bruegge, B., Nickles, J., & Sauer, M. S. (2018) · International Conference on Internet of Things: Systems, Management and Security (IOTSMS) · doi:10.1109/iotsms.2018.8554484 · Cited by 61 · cited 2× · see citing works
“[113], updating IIoT systems is often complex and cumbersome, and requires an expert technician to perform the update, which can be a lengthy process.”
BackgroundSurvey of advances and challenges in intelligent autonomy for distributed cyber‐physical systems
McKee, D. W., Clement, S., Almutairi, J., & Xu, J. (2018) · CAAI Transactions on Intelligence Technology · doi:10.1049/trit.2018.0010 · Cited by 60 · see citing works
Wu, T., Chen, C., Wang, K.-H., & Wu, J. M. (2019) · IEEE Access · doi:10.1109/access.2019.2909040 · Cited by 59 · see citing works
Securing smart maintenance services: Hardware-security and TLS for MQTT
Lesjak, C., Hein, D. M., Hofmann, M., Maritsch, M., Aldrian, A., Priller, P., Ebner, T., Ruprechter, T., & Pregartner, G. (2015) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2015.7281913 · Cited by 55 · see citing works
Efficient certificateless access control for industrial Internet of Things
Li, F., Hong, J., & Omala, A. A. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2016.12.036 · Cited by 55 · cited 2× · see citing works
“[86] propose a certificateless authentication scheme”
BackgroundCyber-Storms Come from Clouds: Security of Cloud Computing in the IoT Era
Donno, M. D., Giaretta, A., Dragoni, N., Bucchiarone, A., & Mazzara, M. (2019) · Future Internet · doi:10.3390/fi11060127 · Cited by 55 · cited 1× · see citing works
“Also, we are aware that a comprehensive and thorough discussion on how Fog computing could tackle the IIoT security requirements would require a dedicated treatment that would result in an entire paper itself, which is out of the scope of this work (for instance, in [255] we focus on how Cloud requirements can impact…”
BackgroundSelf-citationAlcaraz, C., Román, R., Najera, P., & López, J. (2012) · Ad Hoc Networks · doi:10.1016/j.adhoc.2012.12.001 · Cited by 52 · see citing works
Paliwal, S. (2019) · IEEE Access · doi:10.1109/access.2019.2941701 · Cited by 51 · see citing works
Khoda, M. E., Imam, T., Kamruzzaman, J., Gondal, I., & Rahman, A. (2019) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2019.2958530 · Cited by 50 · cited 1× · see citing works
“The findings in [188] agree with this, as also there the authors manage to bypass machine learning systems.”
BackgroundSecurity trends and advances in manufacturing systems in the era of industry 4.0
Chhetri, S. R., Rashid, N., Faezi, S., & Faruque, M. A. A. (2017) · International Conference on Computer Aided Design · doi:10.5555/3199700.3199844 · Cited by 49 · see citing works
The future of data privacy and security concerns in Internet of Things
Solangi, Z. A., Solangi, Y. A., Chandio, S., Aziz, M. S. A., Hamzah, M. S., & Shah, A. (2018) · IEEE International Conference on Innovative Research and Development (ICIRD) · doi:10.1109/icird.2018.8376320 · Cited by 49 · cited 1× · see citing works
“detailed profiles of users, putting their privacy at risk [168].”
BackgroundAn Attribute Credential Based Public Key Scheme for Fog Computing in Digital Manufacturing
Yao, X., Kong, H., Liu, H., Qiu, T., & Ning, H. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2891079 · Cited by 48 · cited 1× · see citing works
“[109] share the sentiment that distributed AC is needed, but propose a Fog solution based on attribute credentials.”
BackgroundSecure Industrial Internet of Things Critical Infrastructure Node Design
McGinthy, J. M., & Michaels, A. J. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2903242 · Cited by 47 · cited 1× · see citing works
“In a comprehensive work, McGinthy and Michaels [242] describe secure architectural frameworks for IIoT and WSN sensor nodes, with security features grouped by energy class.”
BackgroundToward Data Security in Edge Intelligent IIoT
Yu, Y. H., Chen, R., Li, H., Li, Y., & Tian, A. (2019) · IEEE Network · doi:10.1109/mnet.001.1800507 · Cited by 44 · cited 1× · see citing works
“[160].”
Key Distribution Protocol for Industrial Internet of Things Without Implicit Certificates
Eldefrawy, M. H., Pereira, N., & Gidlund, M. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2865212 · Cited by 41 · see citing works
Fully Secure Lightweight Certificateless Signature Scheme for IIoT
Rezaeibagha, F., Mu, Y., Huang, X., Yang, W., & Huang, K. (2019) · IEEE Access · doi:10.1109/access.2019.2944631 · Cited by 41 · see citing works
Smart Contract-Based Data Commodity Transactions for Industrial Internet of Things
Jiang, Y., Zhong, Y. F., & Ge, X. (2019) · IEEE Access · doi:10.1109/access.2019.2959771 · Cited by 41 · cited 1× · see citing works
“for confidential data exchange, while others propose things such as energy trading [150] and big data markets [152].”
BackgroundThe Internet of Hackable Things
Dragoni, N., Giaretta, A., & Mazzara, M. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-70578-1_13 · Cited by 40 · cited 1× · see citing works
“As a matter of fact, IoT devices are often poorly secured [2] and thus easy targets for malware taking advantage of them to run devastating cyber-attacks, such as Distributed Denial of Service (DDoS) [3] (e.”
BackgroundSelf-citationAnomaly Detection in Aging Industrial Internet of Things
Genge, B., Haller, P., & Calin, E. (2019) · IEEE Access · doi:10.1109/access.2019.2920699 · Cited by 40 · cited 1× · see citing works
“[183] note that when monitoring the output of physical processes, care has to be taken to take the gradual decay of processes (e.”
BackgroundEmIr-Auth: Eye Movement and Iris-Based Portable Remote Authentication for Smart Grid
Ma, Z., Yang, Y., Liu, X., Liu, Y., Ma, S., Ren, K., & Yao, C. H. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2946047 · Cited by 40 · cited 1× · see citing works
“Further, it typically requires physical proximity, although recent work [80] shows that remote biometric”
BackgroundSecurity Viewpoint in a Reference Architecture Model for Cyber-Physical Production Systems
Ma, Z., Hudic, A., Shaaban, A. M., & Plósz, S. (2017) · IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) · doi:10.1109/eurospw.2017.65 · Cited by 38 · see citing works
Esposito, C., Castiglione, A., Palmieri, F., & Santis, A. D. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2791956 · Cited by 38 · see citing works
Protecting cyber physical production systems using anomaly detection to enable self-adaptation
Settanni, G., Skopik, F., Karaj, A., Wurzenberger, M., & Fiedler, R. (2018) · IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) · doi:10.1109/icphys.2018.8387655 · Cited by 38 · see citing works
Anomaly Detection Methods for IIoT Networks
Zhou, L., & Guo, H. (2018) · IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) · doi:10.1109/soli.2018.8476769 · Cited by 38 · cited 1× · see citing works
“0, these concepts become crucial as the software and configuration of IIoT systems must have the ability to be changed, in order to provide protection against previously unknown security threats [116].”
BackgroundCovert Channels-Based Stealth Attacks in Industry 4.0
Alcaraz, C., Bernieri, G., Pascucci, F., López, J., & Setola, R. (2019) · IEEE Systems Journal · doi:10.1109/jsyst.2019.2912308 · Cited by 38 · cited 1× · see citing works
“through stealthy injection attacks [196], or to establish covert communication channels, as demonstrated in [172], and should be monitored against.”
BackgroundUAV-enabled friendly jamming scheme to secure industrial Internet of Things
Wang, Q., Dai, H., Wang, H. H., Xu, G., & Sangaiah, A. K. (2019) · Journal of Communications and Networks · doi:10.1109/jcn.2019.000042 · Cited by 37 · see citing works
Optimal and secure protocols in the IETF 6TiSCH communication stack
Accettura, N., & Piro, G. (2014) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie.2014.6864831 · Cited by 35 · cited 1× · see citing works
“in [227].”
Information security aspects of Industry 4.0
Kiss, M., Breda, G., & Muha, L. (2019) · Procedia Manufacturing · doi:10.1016/j.promfg.2019.02.293 · Cited by 35 · see citing works
Architecture, technologies and challenges for cyber-physical systems in industry 4.0
Hofer, F. (2018) · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement · doi:10.1145/3239235.3239242 · Cited by 34 · cited 1× · see citing works
“Another recent study [16] focuses on Industry 4.”
BackgroundAn Efficient Intrusion Detection Model for Edge System in Brownfield Industrial Internet of Things
Al-Hawawreh, M. S., Sitnikova, E., & den Hartog, F. (2019) · International Conference on Big Data and Internet of Things (BDIOT) · doi:10.1145/3361758.3361762 · Cited by 34 · cited 1× · see citing works
“For example, [200] and [203] provide a performance comparison of various machine learning algorithms for detecting anomalies in IIoT, in [171], Al-Hawawreh et al.”
BackgroundMassive-Scale Automation in Cyber-Physical Systems: Vision & Challenges
McKee, D. W., Clement, S., Almutairi, J., & Xu, J. (2017) · International Symposium on Autonomous Decentralized Systems · doi:10.1109/isads.2017.56 · Cited by 33 · see citing works
LUCON: Data Flow Control for Message-Based IoT Systems
Schuette, J., & Brost, G. S. (2018) · doi:10.1109/trustcom/bigdatase.2018.00052 · Cited by 33 · see citing works
Industrial Internet of Things Based Ransomware Detection using Stacked Variational Neural Network
Al-Hawawreh, M. S., & Sitnikova, E. (2019) · International Conference on Big Data and Internet of Things (BDIOT) · doi:10.1145/3361758.3361763 · Cited by 33 · cited 1× · see citing works
“propose a deep neural network approach for use in brownfield installations, in [170] the authors propose a similar system for ransomware detection, and in [197], the authors employ machine learning to detect time synchronization attacks.”
Unmanned Aerial Vehicle security using Recursive parameter estimation
Birnbaum, Z., Dolgikh, A., Skormin, V. A., O'Brien, E., & Müller, D. (2014) · International Conference on Unmanned Aircraft Systems (ICUAS) · doi:10.1109/icuas.2014.6842314 · Cited by 32 · see citing works
Cloud-Centric Collaborative Security Service Placement for Advanced Metering Infrastructures
Hasan, M. M., & Mouftah, H. T. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2763954 · Cited by 32 · cited 3× · see citing works
“Hasan and Mouftah [184] state that latency is one of the major challenges for security monitoring systems, due to the geographical distance between devices in certain Industry 4.”
BackgroundInfluentialPrivacy-Preserving Tensor-Based Multiple Clusterings on Cloud for Industrial IoT
Zhao, Y., Yang, L. T., & Sun, J. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2871174 · Cited by 32 · see citing works
Ankele, R., Marksteiner, S., Nahrgang, K., & Vallant, H. (2019) · International Conference on Availability, Reliability and Security (ARES) · doi:10.1145/3339252.3341482 · Cited by 32 · cited 1× · see citing works
“[83].”
Xyreum: A High-Performance and Scalable Blockchain for IIoT Security and Privacy
Sani, A. S., Yuan, D., Bao, W., Yeoh, P. L., Dong, Z. Y., Vucetic, B. S., & Bertino, E. (2019) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs.2019.00190 · Cited by 31 · cited 1× · see citing works
“[157] propose a privacy preserving blockchain using mutually authenticated encryption”
ENISA Documents in Cybersecurity Assurance for Industry 4.0: IIoT Threats and Attacks Scenarios
Sklyar, V. V., & Kharchenko, V. S. (2019) · IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) · doi:10.1109/idaacs.2019.8924452 · Cited by 31 · see citing works
An AAA solution for securing industrial IoT devices using next generation access control
Kolluru, K. K., Paniagua, C., van Deventer, J., Eliasson, J., Delsing, J., & DeLong, R. (2018) · IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) · doi:10.1109/icphys.2018.8390799 · Cited by 30 · cited 1× · see citing works
“[76] state that mutual authentication between any two IoT devices is necessary, as many of them are exposed to external environments.”
BackgroundLong-Term Driving Behaviour Modelling for Driver Identification
Marchegiani, L., & Posner, I. (2018) · International Conference on Intelligent Transportation Systems · doi:10.1109/itsc.2018.8569610 · Cited by 30 · see citing works
Usman, M., Jan, M. A., Jolfaei, A., Xu, M. G., He, X., & Chen, J. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2952645 · Cited by 30 · see citing works
Leveraging SDN to improve security in industrial networks
Cheminod, M., Durante, L., Seno, L., Valenza, F., Valenzano, A., & Zunino, C. (2017) · IEEE International Workshop on Factory Communication Systems (WFCS) · doi:10.1109/wfcs.2017.7991960 · Cited by 28 · cited 1× · see citing works
“According to [212],”
Nakamura, E. T., & Ribeiro, S. L. (2018) · Global Internet of Things Summit (GIoTS) · doi:10.1109/giots.2018.8534521 · Cited by 28 · cited 2× · see citing works
“In [44] and [126] two risk assess-”
Jiang, X., Pang, Z., Luvisotto, M., Pan, F., Candell, R., & Fischione, C. (2019) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2019.2893037 · Cited by 27 · cited 1× · see citing works
“from the relative distance and direction between transmitters can help in identifying these types of attacks [32].”
BackgroundAddressing security challenges in industrial augmented reality systems
Langfinger, M., Schneider, M., Stricker, D., & Schotten, H. D. (2017) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2017.8104789 · Cited by 26 · see citing works
Secure and Time-sensitive Communication for Remote Process Control and Monitoring
Kobzan, T., Schriegel, S., Althoff, S., Boschmann, A., Otto, J., & Jasperneite, J. (2018) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2018.8502539 · Cited by 26 · cited 1× · see citing works
“would be directly connected on the machine level [219].”
BackgroundLászka, Á., Abbas, W., Vorobeychik, Y., & Koutsoukos, X. (2018) · IEEE International Conference on Industrial Internet (ICII) · doi:10.1109/icii.2018.00025 · Cited by 25 · cited 2× · see citing works
“[126]: redundancy,”
AntibIoTic: Protecting IoT Devices Against DDoS Attacks
Donno, M. D., Dragoni, N., Giaretta, A., & Mazzara, M. (2017) · Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) · Cited by 25 · see citing works
Self-citationOn the Security of an Efficient and Robust Certificateless Signature Scheme for IIoT Environments
Yang, W., Wang, S., Huang, X., & Mu, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2927597 · Cited by 24 · see citing works
MimePot: a Model-based Honeypot for Industrial Control Networks
Bernieri, G., Conti, M., & Pascucci, F. (2019) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2019.8913891 · Cited by 24 · cited 1× · see citing works
“In [176], Bernieri et al.”
AntibIoTic: Protecting IoT Devices Against DDoS Attacks
Donno, M. D., Dragoni, N., Giaretta, A., & Mazzara, M. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-70578-1_7 · Cited by 23 · cited 1× · see citing works
“[260], [261] propose an anti-malware software for IoT and they discuss how the use of Fog computing helps to solve some of the challenges intrinsic in the deployment.”
MethodSelf-citationTowards trustworthy end-to-end communication in industry 4.0
Bicaku, A., Maksuti, S., Palkovits-Rauter, S., Tauber, M., Matischek, R., Schmittner, C., Μαντάς, Γ., Thron, M., & Delsing, J. (2017) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2017.8104889 · Cited by 23 · cited 2× · see citing works
“Its relevancy is underlined by the inclusion of continuous maintenance and maintenance frequency being used as measurable safety indicators in a meta-model proposal for automated security dependability detection within IIoT systems [25].”
BackgroundFormally verified latency-aware VNF placement in industrial Internet of things
Marchetto, G., Sisto, R., Yusupov, J., & Ksentinit, A. (2018) · IEEE International Workshop on Factory Communication Systems (WFCS) · doi:10.1109/wfcs.2018.8402355 · Cited by 23 · cited 1× · see citing works
“[221] state that additionally connectivity and isolation between endpoints are network security requirements, although these can possibly be interpreted as security policies by themselves.”
BackgroundSecrecy Performance Analysis of Wireless Sensor Networks
Ai, Y., Cheffena, M., Ohtsuki, T. O., & Zhuang, H. (2019) · IEEE Sensors Letters · doi:10.1109/lsens.2019.2909323 · Cited by 23 · see citing works
A Reference Architecture for IIoT and Industrial Control Systems Testbeds
Craggs, B., Rashid, A., Hankin, C., Antrobus, R., Serban, O., & Thapen, N. (2019) · Living in the Internet of Things (IoT 2019) · doi:10.1049/cp.2019.0169 · Cited by 23 · cited 1× · see citing works
“[233]”
Security challenges in SCADA systems over Wireless Sensor and Actuator Networks
Januário, F., Carvalho, C., Cardoso, A., & Gil, P. S. (2016) · International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) · doi:10.1109/icumt.2016.7765386 · Cited by 22 · cited 1× · see citing works
“When looking at low-energy devices, WSNs have been identified as a way to increase the robustness of SCADA systems against network failures, due to their distributed and self-organizing nature [125].”
BackgroundSecurity Development Lifecycle for Cyber-Physical Production Systems
Eckhart, M., Ekelhart, A., Lüder, A., Biffl, S., & Weippl, E. R. (2019) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2019.8927590 · Cited by 22 · cited 1× · see citing works
“system, and in [234], Eckhart et al.”
The Internet of Hackable ThingsPreprint
Dragoni, N., Giaretta, A., & Mazzara, M. (2017) · doi:10.31224/osf.io/5ua7g · Cited by 22 · see citing works
Self-citationPropFuzz — An IT-security fuzzing framework for proprietary ICS protocols
Niedermaier, M., Fischer, F., & von Bodisco, A. (2017) · International Conference on Applied Electronics · doi:10.23919/ae.2017.8053600 · Cited by 21 · see citing works
Monitoring Industry 4.0 applications for security and safety standard compliance
Bicaku, A., Schmittner, C., Tauber, M., & Delsing, J. (2018) · IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) · doi:10.1109/icphys.2018.8390801 · Cited by 21 · cited 1× · see citing works
“In [25] and [120], a number of measurable indicator points are identified, among which those relating to resiliency.”
BackgroundPropFuzz — An IT-security fuzzing framework for proprietary ICS protocols
Niedermaier, M., Fischer, F., & von Bodisco, A. (2017) · Digital Library (University of West Bohemia) · Cited by 21 · see citing works
Priller, P., Aldrian, A., & Ebner, T. (2014) · doi:10.1109/etfa.2014.7005136 · Cited by 20 · cited 1× · see citing works
“[117] provide a case study on this subject detailing a number of smart maintenance security requirements, notably the ability to update as well as secure communication channels themselves.”
BackgroundData Protection Compliance Regulations and Implications for Smart Factories of the Future
Preuveneers, D., Joosen, W., & Ilie‐Zudor, E. (2016) · International Conference on Intelligent Environments (IE) · doi:10.1109/ie.2016.15 · Cited by 20 · cited 1× · see citing works
“[50] discuss the implications of the GDPR in Industry 4.”
BackgroundLesjak, C., Ruprechter, T., Haid, J., Bock, H., & Brenner, E. (2014) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2014.7005086 · Cited by 20 · see citing works
Secure multi-cloud virtual network embedding
Alaluna, M., Ferrolho, L., Figueira, J. R., Neves, N., & Ramos, F. M. V. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.03.023 · Cited by 20 · cited 1× · see citing works
“However, with modern Cloud infrastructures, often the network virtualization solutions proposed by Cloud providers constrain customers to that one Cloud service provider [222].”
BackgroundSecurity Considerations in Modular Mobile Manipulation
Dieber, B., & Breiling, B. (2019) · IEEE International Conference on Robotic Computing (IRC) · doi:10.1109/irc.2019.00019 · Cited by 20 · see citing works
The Forgotten I in IIoT: a vulnerability scanner for industrial internet of things
Antrobus, R., Green, B., Frey, S., & Rashid, A. (2019) · IET Living in the Internet of Things (IoT) · doi:10.1049/cp.2019.0126 · Cited by 20 · see citing works
SMAP Fog/Edge: A Secure Mutual Authentication Protocol for Fog/Edge
Pardeshi, M. S., & Yuan, S. (2019) · IEEE Access · doi:10.1109/access.2019.2930814 · Cited by 20 · see citing works
Integrated Cyber Safety & Security Management System: Industry 4.0 Issue
Kharchenko, V. S., Dotsenko, S., Illiashenko, O. A., & Kamenskyi, S. (2019) · International Conference on Dependable Systems, Services and Technologies (DESSERT) · doi:10.1109/dessert.2019.8770010 · Cited by 20 · see citing works
An Evaluation of Machine Learning Algorithms To Detect Attacks in Scada Network
Tamy, S., Belhadaoui, H., Rabbah, M. A., Rabbah, N., & Rifi, M. (2019) · Mediterranean Congress of Telecommunications (CMT) · doi:10.1109/cmt.2019.8931327 · Cited by 20 · cited 1× · see citing works
“For example, [200] and [203] provide a performance comparison of various machine learning algorithms for detecting anomalies in IIoT, in [171], Al-Hawawreh et al.”
BackgroundCurrent Significance of IT-Infrastructure Enabling Industry 4.0 in Large Companies
Autenrieth, P., Lorcher, C., Pfeiffer, C., Winkens, T., & Martin, L. (2018) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice.2018.8436244 · Cited by 19 · see citing works
Mugarza, I., Amurrio, A., Azketa, E., & Jacob, E. (2019) · IEEE Access · doi:10.1109/access.2019.2905925 · Cited by 19 · cited 1× · see citing works
“to a smart city scenario [112].”
Hu, Y., Zhang, D., Cao, G., & Pan, Q. (2019) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2019.8913895 · Cited by 19 · see citing works
Performance evaluation of MAC algorithms for real-time Ethernet communication systems
Czybik, B., Hausmann, S., Heiss, S., & Jasperneite, J. (2013) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2013.6622965 · Cited by 18 · see citing works
Hardware-secured and transparent multi-stakeholder data exchange for industrial IoT
Lesjak, C., Bock, H., Hein, D. M., & Maritsch, M. (2016) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2016.7819251 · Cited by 18 · cited 1× · see citing works
“[40] observe that an often-needed”
An efficient authorization framework for securing industrial Internet of Things
Chen, G., & Ng, W. S. (2017) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon.2017.8228043 · Cited by 18 · cited 1× · see citing works
“In the work presented by Chen and Ng [99], AC and authorization are also identified as one of the major challenges for the IIoT.”
BackgroundHoeller, A., & Toegl, R. (2018) · IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) · doi:10.1109/eurospw.2018.00026 · Cited by 18 · cited 1× · see citing works
“References [17], [95], and [97] all identify the need for remote attestation, in order to increase the system’s resilience against intruders.”
BackgroundConzon, D., Rashid, M. R. A., Tao, X., Soriano, Á., Nicholson, R., & Ferrera, E. (2019) · International Conference on Computing, Communication and Security (ICCCS) · doi:10.1109/cccs.2019.8888136 · Cited by 18 · cited 2× · see citing works
“[165] describe a modelbased framework for IoT, the security and privacy principles of which are derived from the GDPR.”
BackgroundKadera, P., & Novák, P. (2016) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2016.2601918 · Cited by 17 · cited 2× · see citing works
“expansion of the World Wide Web [187].”
Context-Aware Authentication: State-of-the-Art Evaluation and Adaption to the IIoT
Loske, M., Rothe, L., & Gertler, D. G. (2019) · IEEE World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2019.8767327 · Cited by 17 · cited 1× · see citing works
“[79] survey the available literature on this so-called context-aware authentication.”
BackgroundPrevention of false data injections in smart infrastructures
Krundyshev, V., & Kalinin, M. (2019) · IEEE International Black Sea Conference on Communications and Networking · doi:10.1109/blackseacom.2019.8812786 · Cited by 17 · see citing works
Towards flexible and secure end-to-end communication in industry 4.0
Maksuti, S., Bicaku, A., Tauber, M., Palkovits-Rauter, S., Haas, S., & Delsing, J. (2017) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2017.8104888 · Cited by 16 · cited 1× · see citing works
“[42] take a more flexible stance than Shaabany, observing that security and business process performance will always come at the cost of each other.”
BackgroundA Policy Checker Approach for Secure Industrial SDN
Melis, A., Berardi, D., Contoli, C., Callegati, F., Esposito, F., & Prandini, M. (2018) · Cyber Security in Networking Conference (CSNet) · doi:10.1109/csnet.2018.8602927 · Cited by 16 · cited 1× · see citing works
“[191] propose a live monitoring solution of flow permission controls, as well as a proactive formal verification mechanism of the security policies in SDN systems.”
BackgroundFormal Security Verification of Industry 4.0 Applications
Nigam, V., & Talcott, C. (2019) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2019.8869428 · Cited by 16 · cited 1× · see citing works
“In [144], the authors propose a symbolic analysis model that can identify such messages.”
BackgroundSEC-BlockEdge: Security Threats in Blockchain-Edge based Industrial IoT Networks
Kumar, T., Braeken, A., Ramani, V., Ahmad, I., Harjula, E., & Ylianttila, M. (2019) · International Workshop on Resilient Networks Design and Modeling (RNDM) · doi:10.1109/rndm48015.2019.8949107 · Cited by 16 · cited 1× · see citing works
“For a more thorough discussion on security requirements and challenges for blockchain in the IIoT, we refer the interested reader to [35], and for a discussion on risky characteristics common to blockchain technologies we point to [158].”
BackgroundPulSec: Secure Element based framework for sensors anomaly detection in Industry 4.0
Deshpande, V. M., George, L., & Badis, H. (2019) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2019.11.362 · Cited by 16 · cited 1× · see citing works
“[179] propose a heartbeat protocol catering specifically to WSNs, ensuring that overhead on the sensor level is minimal.”
BackgroundLesjak, C., Ruprechter, T., Bock, H., Haid, J., & Brenner, E. (2014) · International Conference for Internet Technology and Secured Transactions · doi:10.1109/icitst.2014.7038800 · Cited by 15 · cited 2× · see citing works
“[36] reason that smart maintenance requires”
BackgroundSecuring the Industrial Internet of Things for Critical Infrastructure (IIoT-CI)
O'Raw, J., Laverty, D., & Morrow, D. J. (2019) · 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2019.8767279 · Cited by 15 · cited 1× · see citing works
“Other points where SDNs can improve system security are discussed in [217].”
BackgroundImproving an Identity Authentication Management Protocol in IIoT
AlAbdullatif, A., AlAjaji, K., Al-Serhani, N. S., Zagrouba, R., & Aldossary, M. M. (2019) · International Conference on Computer Applications & Information Security (ICCAIS) · doi:10.1109/cais.2019.8769499 · Cited by 15 · cited 1× · see citing works
“A different approach is taken in [60], where the blockchain-based BCTrust protocol is extended with key management functionality.”
MethodInterledger for the Industrial Internet of Things
Nikander, P., Autiosalo, J., & Paavolainen, S. (2019) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin41052.2019.8972167 · Cited by 15 · cited 1× · see citing works
“[156], who discuss throughput, latency, and resource requirements more in-depth.”
BackgroundDetermining a security roadmap for the microelectronics industry
Moyne, J. R., Mashiro, S., & Gross, D. R. (2018) · Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) · doi:10.1109/asmc.2018.8373213 · Cited by 14 · cited 2× · see citing works
“[49], [71], [133], [136]).”
Modeling of dynamic trust contracts for industry 4.0 systems
Al-Ali, R., Heinrich, R., Hnětynka, P., Juan-Verdejo, A., Seifermann, S., & Walter, M. (2018) · European Conference on Software Architecture · doi:10.1145/3241403.3241450 · Cited by 14 · cited 1× · see citing works
“[162] describe a real-world use case for data flow monitoring, where certain data on machine error rates is shared within the company itself, and across organization boundaries based on a set of privacy policies.”
BackgroundA Comparative Study on Virtual Private Networks for Future Industrial Communication Systems
Lackorzynski, T., Köpsell, S., & Strufe, T. (2019) · IEEE International Workshop on Factory Communication Systems (WFCS) · doi:10.1109/wfcs.2019.8758010 · Cited by 14 · cited 1× · see citing works
“[220] compare multiple readily available VPN solutions on metrics important to industrial appliances.”
BackgroundA Unified Architecture for Industrial IoT Security Requirements in Open Platform Communications
Hansch, G., Schneider, P., Fischer, K., & Böttinger, K. (2019) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2019.8869524 · Cited by 14 · see citing works
Preuveneers, D., Joosen, W., & Ilie‐Zudor, E. (2017) · Symposium on Applied Computing · doi:10.1145/3019612.3019861 · Cited by 13 · see citing works
Challenges in assurance case application for industrial IoT
Sklyar, V. V., & Kharchenko, V. S. (2017) · IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) · doi:10.1109/idaacs.2017.8095187 · Cited by 13 · cited 1× · see citing works
“Another example can be found in [89], where the challenges in applying the Assurance Case methodology for the IIoT are laid out.”
MethodShaabany, G., & Anderl, R. (2018) · International Conference on System Science and Engineering · doi:10.1109/icsse.2018.8520195 · Cited by 13 · cited 1× · see citing works
“Shaabany and Anderl [51] states that software and hardware should be designed carefully, with security in mind, in order to reduce the attack surface as much as possible during design time.”
BackgroundAn Efficient Image Encryption Scheme for Industrial Internet-of-Things Devices
Zhang, M., Peng, B., & Chen, Y. (2019) · doi:10.1145/3338507.3358620 · Cited by 13 · see citing works
Flagged first, then by citations
1 of the 251 references couldn’t be matched to a known paper.
Research works printed but not linked: 4
- M. De Donno, N. Dragoni, A. Giaretta, and A. Spognardi, "Analysis of DDoS-sapable IoT malwares," in Proc. IEEE Feder. Conf. Comput. Sci. Inf. Syst. (FedCSIS), 2017, pp. 807-816.
- O. Bergmann, S. Gerdes, and C. Bormann, "Simple keys for sim- ple smart objects," in Proc. Workshop Smart Object Security, 2012, pp. 172-182.
- U. Hunkeler, H. L. Truong, and A. Stanford-Clark, "MQTT-S-A pub- lish/subscribe protocol for wireless sensor networks," in Proc. 3rd Int. Conf. Commun. Syst. Softw. Middleware Workshops (COMSWARE), 2008, pp. 791-798.
- A. Bluschke et al., "FastVPN-Secure and flexible networking for industry 4.0," in Proc. 12th ITG Symp. Broadband Coverage Germany, 2018, pp. 1-8. [Online]. Available: https://imld.de/en/research/research-projects/fastvpn/
Cited by
Sorted by citations
Industry 5.0: A survey on enabling technologies and potential applications
Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890 · see citing works
A Survey on Metaverse: Fundamentals, Security, and Privacy
Wang, Y., Su, Z., Zhang, N., Xing, R., Liu, D., Luan, T. H., & Shen, X. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3202047 · Cited by 1,655 · see citing works
“, from Section III to Section IX), based on existing surveys [42], [43], we classify a broad scope of security threats in the metaverse from the following seven dimensions: authentication & access control, data management, privacy, network, economy, physical/social effects, and governance.”
BackgroundJia, B., Zhang, X., Liu, J., Zhang, Y., Huang, K., & Liang, Y. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3085960 · Cited by 351 · see citing works
Edge computing for Industry 5.0: fundamental, applications and research challenges
Sharma, M., Tomar, A., & Hazra, A. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3359297 · Cited by 312 · see citing works
“Table II summarizes the evolution of edge computing in Industry 5.0 [32].”
BackgroundInfluentialAl-Hawawreh, M. S., Sitnikova, E., & Aboutorab, N. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3102056 · Cited by 285 · see citing works
Fusion of Federated Learning and Industrial Internet of Things: A survey
Boobalan, P., Ramu, S. P., Pham, Q., Dev, K., Pandya, S., Maddikunta, P. K. R., Gadekallu, T. R., & Huynh‐The, T. (2022) · Computer Networks · doi:10.1016/j.comnet.2022.109048 · Cited by 321 · see citing works
“More recently, a survey on IIoT security and the application of edge/fog computing is presented in [19].”
Onu, P., Pradhan, A., & Mbohwa, C. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2022.12.282 · Cited by 280 · see citing works
Walia, G. K., Kumar, M., & Gill, S. S. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3338015 · Cited by 299 · see citing works
Moustafa, N., Koroniotis, N., Keshk, M., Zomaya, A. Y., & Tari, Z. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3280465 · Cited by 266 · see citing works
“Fog computing is an extension of cloud computing that distributes the benefits of the cloud closer to the IoT and across five layers of the IoT [1].”
BackgroundSmart healthcare IoT applications based on fog computing: architecture, applications and challenges
Khanh, Q. V., Hau, N. V., Anh, D. V., & Ngoc, L. A. (2021) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00582-9 · Cited by 205 · see citing works
“In recent times, fog computing has been proposed [19–21].”
BackgroundEdge Computing and Cloud Computing for Internet of Things: A Review
Andriulo, F. C., Fiore, M., Mongiello, M., Traversa, E., & Zizzo, V. (2024) · Informatics · doi:10.3390/informatics11040071 · Cited by 249 · see citing works
“Tange et al. [15] concentrate on the security requirements of the Industrial Internet of Things (IIoT) and how fog computing can be leveraged to address these requirements and thus improve the security of the IIoT.”
Energy-Efficient Fog Computing for 6G-Enabled Massive IoT: Recent Trends and Future Opportunities
Malik, U. M., Javed, M. A., Zeadally, S., & Islam, S. U. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3068056 · Cited by 200 · see citing works
Ali, S., Li, Q., & Yousafzai, A. (2023) · Ad Hoc Networks · doi:10.1016/j.adhoc.2023.103320 · Cited by 216 · see citing works
Consumer, Commercial, and Industrial IoT (In)Security: Attack Taxonomy and Case Studies
Xenofontos, C., Zografopoulos, I., Konstantinou, C., Jolfaei, A., Khan, M. K., & Choo, K.-K. R. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3079916 · Cited by 183 · see citing works
“BLE is extensively used for both wearable as well as industrial IoT (IIoT) ecosystems.”
BackgroundInfluentialIndustrial Internet of Things enabled technologies, challenges, and future directions
Ahmed, S. F., Alam, M. S. B., Hoque, M., Lameesa, A., Afrin, S., Farah, T., Kabir, M., Shafiullah, G., & Muyeen, S. M. (2023) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2023.108847 · Cited by 180 · see citing works
Deep Learning in Security of Internet of Things
Li, Y., Zuo, Y., Song, H. H., & Lv, Z. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3106898 · Cited by 176 · see citing works
“In fact, the low level of security development of IoT is one of the main obstacles hindering its widespread adoption [11].”
BackgroundA Review of Cybersecurity Guidelines for Manufacturing Factories in Industry 4.0
Mullet, V., Sondi, P., & Ramat, E. (2021) · IEEE Access · doi:10.1109/access.2021.3056650 · Cited by 161 · see citing works
“A more specific recent survey [9] reviewed 262 papers regarding every aspect of Industry 4.0 security.”
BackgroundInfluentialArtificial Intelligence-Based Cyber Security in the Context of Industry 4.0—A Survey
de Azambuja, A. J. G., Plesker, C., Schützer, K., Anderl, R., Schleich, B., & Almeida, V. R. (2023) · Electronics · doi:10.3390/electronics12081920 · Cited by 156 · see citing works
“Tange et al. [68] show a systematic review with a focus on the security requirements of the IoT device.”
BackgroundUpgrading the manufacturing sector via applications of Industrial Internet of Things (IIoT)
Javaid, M., Haleem, A., Singh, R. P., Rab, S., & Suman, R. (2021) · Sensors International · doi:10.1016/j.sintl.2021.100129 · Cited by 154 · see citing works
Data Security in Healthcare Industrial Internet of Things With Blockchain
Khan, A. A., Bourouis, S., Kamruzzaman, M. M., Hadjouni, M., Shaikh, Z. A., Laghari, A. A., Elmannai, H., & Dhahbi, S. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3273851 · Cited by 141 · see citing works
An Energy-Efficient Data Aggregation Mechanism for IoT Secured by Blockchain
Ahmed, A., Abdullah, S., Bukhsh, M., Ahmad, I., & Mushtaq, Z. (2022) · IEEE Access · doi:10.1109/access.2022.3146295 · Cited by 133 · see citing works
An Ensemble Learning Based Intrusion Detection Model for Industrial IoT Security
Mohy-eddine, M., Guezzaz, A., Benkirane, S., Azrour, M., & Farhaoui, Y. (2023) · Big Data Mining and Analytics · doi:10.26599/bdma.2022.9020032 · Cited by 139 · see citing works
Alotaibi, B. (2023) · doi:10.20944/preprints202307.0771.v1 · Cited by 128 · see citing works
“…is preferable to utilize edge computing devices to ascertain the validity of these updates and run thorough tests (e.g., running the updates needed for the industrial systems at the edge in a sandbox environment to ensure no anomalies reside before forwarding them to the industrial devices) [10].”
BackgroundInfluentialEdge Intelligence for Data Handling and Predictive Maintenance in IIOT
Hafeez, T., Xu, L., & McArdle, G. (2021) · IEEE Access · doi:10.1109/access.2021.3069137 · Cited by 124 · see citing works
“Lastly, as data privacy and security have been hindering the adoption of IIoT [102], not all production facilities will be willing to store confi-dential data in the cloud.”
BackgroundScheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions
Goudarzi, M., Palaniswami, M. S., & Buyya, R. (2022) · ACM Computing Surveys · doi:10.1145/3544836 · Cited by 122 · see citing works
“In addition, FSs are more exposed to end-users which makes them potentially less-secured compared to CSs [126].”
BackgroundSecurity Threats, Countermeasures, and Challenges of Digital Supply Chains
Hammi, B., Zeadally, S., & Nebhen, J. (2023) · ACM Computing Surveys · doi:10.1145/3588999 · Cited by 112 · see citing works
“Several surveys [9][10] [11][12] have discussed diferent security issues and countermeasures related to these techniques and technologies such as Industrial Internet of Things or SCADA systems.”
BackgroundCybersecurity for Industrial IoT (IIoT): Threats, countermeasures, challenges and future directions
Mekala, S. H., Baig, Z., Anwar, A., & Zeadally, S. (2023) · Computer Communications · doi:10.1016/j.comcom.2023.06.020 · Cited by 111 · see citing works
A Comprehensive Study on LPWANs With a Focus on the Potential of LoRa/LoRaWAN Systems
Milarokostas, C., Tsolkas, D., Passas, N. I., & Merakos, L. F. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3229846 · Cited by 116 · see citing works
“ical entity with a digital one and allow the flow of data between them, the DT concept is expected to play a major role in the realization of Industrial IoT (IIoT) [61], [62] and”
BackgroundHealthcare Internet of Things: Security Threats, Challenges, and Future Research Directions
Adil, M., Khan, M. K., Kumar, N., Attique, M., Farouk, A., Guizani, M., & Jin, Z. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3360289 · Cited by 113 · see citing works
“Tange et al. [124] explained the susceptibility and security concerns interlinked with HC-IoT networks by assuming different operational aspects of interconnected devices in the network.”
BackgroundFog computing security and privacy for the Internet of Thing applications: State‐of‐the‐art
Alzoubi, Y. I., Osmanaj, V., Jaradat, A., & Al‐Ahmad, A. (2020) · Security and Privacy · doi:10.1002/spy2.145 · Cited by 108 · see citing works
Key Challenges and Emerging Technologies in Industrial IoT Architectures: A Review
Mirani, A. A., Velasco-Hernandez, G., Awasthi, A., & Walsh, J. (2022) · Sensors · doi:10.3390/s22155836 · Cited by 119 · see citing works
“According to [59], fog computing addresses the security and privacy issues in the IIoT, while the authors in [60] highlight the features of blockchain for solving the security and privacy issues.”
BackgroundKornaros, G. (2022) · IEEE Access · doi:10.1109/access.2022.3179047 · Cited by 106 · see citing works
“Fog computing, as a rising computing paradigm along with SDN and NFV technologies, can become a powerful solution in securing a variety of connected industrial environments [167].”
Cross-Layer Device Authentication With Quantum Encryption for 5G Enabled IIoT in Industry 4.0
Xu, D., Yu, K., & Ritcey, J. A. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3130163 · Cited by 93 · see citing works
Kumar, P., Gupta, G. P., Tripathi, R., Garg, S., & Hassan, M. M. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3122368 · Cited by 90 · see citing works
“devices used in maritime world is rapidly increasing [1], [2].”
BackgroundBlockchain-based decentralized trust management in IoT: systems, requirements and challenges
Arshad, Q., Khan, W. Z., Azam, F., Khan, M. K., Yu, H., & Zikria, Y. B. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01058-8 · Cited by 88 · see citing works
An effective intrusion detection approach based on ensemble learning for IIoT edge computing
Mohy-eddine, M., Guezzaz, A., Benkirane, S., & Azrour, M. (2022) · Journal of Computer Virology and Hacking Techniques · doi:10.1007/s11416-022-00456-9 · Cited by 88 · see citing works
“IIoT is considered an evolution of IoT that aims to increase the level of automation by integrating cloud and edge computing [10].”
BackgroundPrivacy-Preserving federated learning in medical diagnosis with homomorphic re-Encryption
Ku, H., Susilo, W., Zhang, Y., Liu, W., & Zhang, M. (2021) · Computer Standards & Interfaces · doi:10.1016/j.csi.2021.103583 · Cited by 81 · see citing works
A revocable and outsourced multi-authority attribute-based encryption scheme in fog computing
Tu, S., Waqas, M. M., Huang, F., Abbas, G., & Abbas, Z. H. (2021) · Computer Networks · doi:10.1016/j.comnet.2021.108196 · Cited by 78 · see citing works
A Holistic Review of Machine Learning Adversarial Attacks in IoT Networks
Khazane, H., Ridouani, M., Salahdine, F., & Kaabouch, N. (2024) · Future Internet · doi:10.3390/fi16010032 · Cited by 85 · see citing works
Kebande, V. R., & Awad, A. I. (2023) · ACM Computing Surveys · doi:10.1145/3635030 · Cited by 75 · see citing works
Hoang, V.-T., Ergu, Y. A., Nguyen, V.-L., & Chang, R. (2024) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2024.104031 · Cited by 72 · see citing works
Heterogeneous Network Access and Fusion in Smart Factory: A Survey
Xia, D., Jiang, C. S., Wan, J., Jin, J., Leung, V. C. M., & Martínez-García, M. (2022) · ACM Computing Surveys · doi:10.1145/3530815 · Cited by 70 · see citing works
“Current [19] [7] [17] [15] [11] [22] [16] [23] [14] [8] [24]”
BackgroundΛαμπρόπουλος, Γ., & Siakas, K. V. (2022) · Journal of Software Evolution and Process · doi:10.1002/smr.2494 · Cited by 72 · see citing works
Blockchain-Based Federated Learning: A Survey and New Perspectives
Ning, W., Zhu, Y., Song, C., Li, H., Zhu, L., Xie, J., Chen, T., Xu, T., Xi, X., & Gao, J. (2024) · Applied Sciences · doi:10.3390/app14209459 · Cited by 69 · see citing works
A survey on security and cryptographic perspective of Industrial-Internet-of-Things
Mishra, N., Islam, S. H., & Zeadally, S. (2023) · Internet of Things · doi:10.1016/j.iot.2023.101037 · Cited by 68 · see citing works
Cederbladh, J., Cicchetti, A., & Suryadevara, J. (2023) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3631976 · Cited by 65 · see citing works
Industrial IoT Intrusion Detection via Evolutionary Cost-Sensitive Learning and Fog Computing
Telikani, A., Shen, J., Yang, J., & Wang, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3188224 · Cited by 64 · see citing works
“Security and privacy issues are two main challenges in IIoT because these networks thereon are established based on the conventional unsecured Internet model [1].”
BackgroundAn Autonomic Workload Prediction and Resource Allocation Framework for Fog-Enabled Industrial IoT
Kumar, M., Kishor, A., Samriya, J. K., & Zomaya, A. Y. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3235107 · Cited by 64 · see citing works
“Fog computing retains the data and computational devices closest to the end users, thus, decreasing the latency time significantly [5].”
BackgroundCMAF-IIoT: Chaotic map-based authentication framework for Industrial Internet of Things
Tanveer, M., Badshah, A. A., Khan, A. U., Alasmary, H., & Chaudhry, S. A. (2023) · Internet of Things · doi:10.1016/j.iot.2023.100902 · Cited by 64 · see citing works
Potential Identity Resolution Systems for the Industrial Internet of Things: A Survey
Ren, Y., Xie, R., Yu, F. R., Huang, T., & Liu, Y. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3045136 · Cited by 63 · see citing works
“Service block in IIoT will bring more serious consequences than consumer IoT [53].”
BackgroundInfluentialAlex, C., Creado, G., Almobaideen, W. A., Alghanam, O. A., & Saadeh, M. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103283 · Cited by 63 · see citing works
Meeting the Requirements of Internet of Things: The Promise of Edge Computing
Hazra, A., Kalita, A., & Gurusamy, M. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3339492 · Cited by 62 · see citing works
“As edge computing becomes a more common computing paradigm, it is increasingly used in next-generation IoT applications [139].”
Federated learning for green and sustainable 6G IIoT applications
Khanh, Q. V., Nguyen, D. C., Anh, D. V., & Quý, N. M. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101061 · Cited by 66 · see citing works
Dynamic Network Slicing Orchestration for Remote Adaptation and Configuration in Industrial IoT
Ji, L., He, S., Wu, W., Gu, C., Bi, J., & Shi, Z. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3131355 · Cited by 61 · see citing works
Zeb, S., Mahmood, A., Khowaja, S. A., Dev, K., Hassan, S. A., Gidlund, M., & Bellavista, P. (2023) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2023.103796 · Cited by 53 · see citing works
Kebande, V. R. (2022) · Forensic Science International Reports · doi:10.1016/j.fsir.2022.100257 · Cited by 58 · see citing works
Lightweight Sybil Attack Detection in IoT based on Bloom Filter and Physical Unclonable Function
Pu, C., & Choo, K. R. (2021) · Computers & Security · doi:10.1016/j.cose.2021.102541 · Cited by 59 · see citing works
DDoS attacks in Industrial IoT: A survey
Chaudhary, S., & Mishra, P. K. (2023) · Computer Networks · doi:10.1016/j.comnet.2023.110015 · Cited by 58 · see citing works
Anomaly Detection in a Smart Industrial Machinery Plant Using IoT and Machine Learning
Jaramillo-Alcázar, Á., Govea, J., & Villegas-Ch, W. E. (2023) · Sensors · doi:10.3390/s23198286 · Cited by 58 · see citing works
“• Key Management: Key management involves the generation, secure storage, and periodic rotation of encryption keys used in the IoT network [23].”
BackgroundSecuring IT/OT Links for Low Power IIoT Devices: Design Considerations for Industry 4.0
Mantravadi, S., Schnyder, R., Møller, C., & Brunoe, T. D. (2020) · IEEE Access · doi:10.1109/access.2020.3035963 · Cited by 57 · see citing works
“A systematic literature review of IIoT security requirements is presented in [24].”
BackgroundAnalysis of Consumer IoT Device Vulnerability Quantification Frameworks
Baho, S. A., & Abawajy, J. (2023) · Electronics · doi:10.3390/electronics12051176 · Cited by 58 · see citing works
“We constructed the keywords for searching the databases from our research questions based on altered PICOC criteria, as in [59].”
MethodDeploying Industry 5.0 drivers to enhance sustainable supply chain risk resilience
Hsu, C.-H., Wu, J.-Z., Zhang, T.-Y., & Chen, J. (2024) · International Journal of Sustainable Engineering · doi:10.1080/19397038.2024.2327381 · Cited by 57 · see citing works
“0 will humanise manufacturing (Tange et al. 2020).”
Haloui, D., Oufaska, K., Oudani, M., & Yassini, K. E. (2024) · Sustainability · doi:10.3390/su16093507 · Cited by 61 · see citing works
“Security, safety, reliability, resilience, and privacy are the five characteristics that influence trust decisions in an IIoT deployment the most [87].”
BackgroundLu, K., Huang, J., Zeng, G., Chen, M.-R., Geng, G., & Weng, J. (2025) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2025.3545363 · Cited by 58 · see citing works
“While IIoT creates opportunities for modern industry, it also introduces serious and evolving security threats, which can be viewed as one of the most important problems to be solved [1], [2].”
Overview of AI-Models and Tools in Embedded IIoT Applications
Dini, P., Diana, L., Elhanashi, A., & Saponara, S. (2024) · Electronics · doi:10.3390/electronics13122322 · Cited by 55 · see citing works
Foukalas, F., & Tziouvaras, A. (2021) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2020.3026837 · Cited by 54 · see citing works
Akbari, M. R., Barati, H., & Barati, A. (2022) · Computing · doi:10.1007/s00607-021-01048-z · Cited by 54 · see citing works
“Therefore, the fog computing model can reduce data traffic sent to servers for data processing and the number of data transmission in the networks [5,6].”
MethodIndustrial cyber-physical systems protection: A methodological review
Canonico, R., & Sperlí, G. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103531 · Cited by 62 · see citing works
Al-Hawawreh, M. S., Alazab, M., Ferrag, M. A., & Hossain, M. S. (2023) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2023.103809 · Cited by 53 · see citing works
A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT
Sun, D., Hu, J., Wu, H., Wu, J. X., Yang, J. Y., Sheng, Q. Z., & Dustdar, S. (2023) · ACM Computing Surveys · doi:10.1145/3612918 · Cited by 56 · see citing works
“[222] comprehensively introduced the security requirements as CIA (i.”
BackgroundA Software Architecture for the Industrial Internet of Things—A Conceptual Model
Ungurean, I., & Gaitan, N. C. (2020) · Sensors · doi:10.3390/s20195603 · Cited by 52 · see citing works
Seid, A. M., Abishu, H. N., Yacob, Y. H., Ayall, T. A., Erbad, A., & Guizani, M. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3197309 · Cited by 51 · see citing works
“These MDs run mission-critical and ultra-low latency applications/services like online gaming, augmented/virtual reality, and image/video encoding to provide broader, advanced, and automated controls in industries like aerospace, defense, healthcare, and energy [6], [7], [8].”
BackgroundAslam, M. M., Tufail, A., Apong, R. A. A. H. M., Silva, L. C. D., & Raza, M. T. (2024) · IEEE Access · doi:10.1109/access.2024.3394848 · Cited by 54 · see citing works
“Authors in [64] presented a survey based on practical IoT systems [11], [69].”
BackgroundAdaptive Network Slicing in Multi-Tenant 5G IoT Networks
Escolar, A. M., Calero, J. M. A., Salvá-García, P., Bernabé, J. B., & Wang, Q. (2021) · IEEE Access · doi:10.1109/access.2021.3051940 · Cited by 51 · see citing works
“This leads to a productivity boost and cost savings in time and money [39].”
BackgroundMemory-Efficient Deep Learning for Botnet Attack Detection in IoT Networks
Popoola, S. I., Adebisi, B., Ande, R., Hammoudeh, M. A. A., & Atayero, A. A. A. (2021) · Electronics · doi:10.3390/electronics10091104 · Cited by 49 · see citing works
“A large number of connected IoT devices are insecure because their default usernames and passwords remain unchanged [5,6].”
BackgroundButt, M. A., Qayyum, A., Ali, H. M., Al‐Fuqaha, A., & Qadir, J. (2022) · Computers & Security · doi:10.1016/j.cose.2022.103058 · Cited by 51 · see citing works
A Cross-Layer Survey on Secure and Low-Latency Communications in Next-Generation IoT
Martalò, M., Pettorru, G., & Atzori, L. (2024) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2024.3390543 · Cited by 51 · see citing works
“Security requirements and challenges in Fog-assisted IIoT networks are investigated in [22].”
BackgroundA genetic-based approach for service placement in fog computing
Sarrafzade, N., Entezari‐Maleki, R., & Sousa, L. A. (2022) · The Journal of Supercomputing · doi:10.1007/s11227-021-04254-w · Cited by 49 · see citing works
“This way, the issue can be investigated without disturbing other operations [11].”
BackgroundA Hybrid Intelligent Framework to Combat Sophisticated Threats in Secure Industries
Javeed, D., Gao, T., Khan, M. T., & Shoukat, D. (2022) · Sensors · doi:10.3390/s22041582 · Cited by 47 · see citing works
“It then uses various software to perform deep analytics and transform vast amounts of data into powerful insights and intelligence [1].”
MethodMehdiabadi, A., Shahabi, V., Shamsinejad, S., Amiri, M., Spulbar, C. M., & Birău, R. (2022) · Applied Sciences · doi:10.3390/app12105126 · Cited by 47 · see citing works
“0 will bring the human touch back to the manufacturing industry [22].”
Systematic Review of Authentication and Authorization Advancements for the Internet of Things
Trnka, M., Abdelfattah, A. S., Shrestha, A., Coffey, M., & Cerny, T. (2022) · Sensors · doi:10.3390/s22041361 · Cited by 44 · see citing works
“Tange et al. [10] 2020 Focused survey on industrial IoT security issues.”
BackgroundDing, X., Zhang, Y., Li, J., Mao, B., Guo, Y., & Li, G. (2023) · Internet of Things · doi:10.1016/j.iot.2023.100689 · Cited by 44 · see citing works
Securing fog-assisted IoT smart homes: a federated learning-based intrusion detection approach
Bensaid, R., Labraoui, N., Saidi, H., & Salameh, H. B. (2024) · Cluster Computing · doi:10.1007/s10586-024-04711-0 · Cited by 44 · see citing works
Mezair, T., Djenouri, Y., Belhadi, A., Srivastava, G., & Lin, J. C. (2022) · Computer Communications · doi:10.1016/j.comcom.2022.02.010 · Cited by 43 · see citing works
Communications Security in Industry X: A Survey
Ahmad, I., Rodriguez, F., Kumar, T., Suomalainen, J., Jagatheesaperumal, S. K., Walter, S., Asghar, M. Z., Li, G., Papakonstantinou, N., Ylianttila, M., et al. (2024) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2024.3356076 · Cited by 42 · see citing works
“Furthermore, a systematic survey on the security of IIoT with requirements and opportunities presented by fog computing is provided in [44].”
BackgroundInfluentialSecurity Perspective Analysis of Industrial Cyber Physical Systems (I-CPS): A Decade-wide Survey
Agrawal, N., & Kumar, R. (2022) · ISA Transactions · doi:10.1016/j.isatra.2022.03.018 · Cited by 42 · see citing works
Orman, A. (2025) · Applied Sciences · doi:10.3390/app15063121 · Cited by 41 · see citing works
“To mitigate these risks, intrusion detection systems (IDSs) are critical in identifying anomalous network traffic, enabling proactive security measures [6].”
Jiang, J., Lin, C., Han, G., Abu-Mahfouz, A. M. I., Shah, S. B. H., & Martínez-García, M. (2022) · Digital Communications and Networks · doi:10.1016/j.dcan.2022.07.001 · Cited by 41 · see citing works
Traffic-Aware Reliable Scheduling in TSCH Networks for Industry 4.0: A Systematic Mapping Review
Tabouche, A., Djamaa, B., & Senouci, M. R. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3302157 · Cited by 41 · see citing works
“This in turn can offer unprecedented application opportunities, ranging from automatic updates/configurations and reliable task monitoring to real-time security applications and critical emergency response systems [5].”
BackgroundMethodSecurity and privacy of industrial big data: Motivation, opportunities, and challenges
Anjum, N., Latif, Z., & Chen, H. (2025) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2025.104130 · Cited by 41 · see citing works
Reliable Internet of Things: Challenges and Future Trends
Khan, M. Z., Alhazmi, O. H., Javed, M. A., Ghandorh, H., & Aloufi, K. S. (2021) · Electronics · doi:10.3390/electronics10192377 · Cited by 41 · see citing works
“A survey of recent security techniques useful for industrial settings is presented in [107].”
BackgroundTABI: Trust-Based ABAC Mechanism for Edge-IoT Using Blockchain Technology
Pathak, A., Al‐Anbagi, I., & Hamilton, H. J. (2023) · IEEE Access · doi:10.1109/access.2023.3265349 · Cited by 43 · see citing works
“and trust management for security purposes [1], [2], [3], [4],”
BackgroundCybertwin-Driven Resource Provisioning for IoE Applications at 6G-Enabled Edge Networks
Adhikari, M., Ambigavathi, M., Kumar, N., & Srirama, S. N. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3096672 · Cited by 39 · see citing works
“Besides that, some of the important resource provisioning strategies along with their research outcomes for processing and analyzing real-time applications at fog/edge networks are highlighted in [19]–[21].”
BackgroundKerimkhulle, S. Y., Dildebayeva, Z., Tokhmetov, A., Amirova, A., Tussupov, J., Махажанова, У., Адалбек, А., Taberkhan, R., Zakirova, A., & Salykbayeva, A. (2023) · Symmetry · doi:10.3390/sym15101958 · Cited by 37 · see citing works
“The same review article [3] provides a systematic literature review on IIoT security from 2011 until 2019, focusing on IIoT security requirements.”
Quo Vadis Industry 4.0? Position, Trends, and Challenges
Leitão, P., Pires, F., Karnouskos, S., & Colombo, A. W. (2020) · IEEE Open Journal of the Industrial Electronics Society · doi:10.1109/ojies.2020.3031660 · Cited by 38 · see citing works
“This implies, for instance, the development of new algorithms for encryption, authentication/authorization, attack detection, etc., that increasingly takes into consideration the unique characteristics, needs, and emerging trends on infrastructures for ICPS [70].”
BackgroundInfluentialFog Computing Based on Machine Learning: A Review
Samann, F. E. F., Abdulazeez, A. M., & Askar, S. K. (2021) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v15i12.21313 · Cited by 37 · see citing works
“The first one is device-driven intelligence, as the IoT devices and the fog layers are getting smarter by adding sensing, more computing power, storage, and communications abilities [56].”
BackgroundDeep Reinforcement Learning for Scheduling in an Edge Computing‐Based Industrial Internet of Things
Wu, J., Zhang, G., Nie, J., Peng, Y., & Zhang, Y. (2021) · Wireless Communications and Mobile Computing · doi:10.1155/2021/8017334 · Cited by 36 · see citing works
Edge intelligence secure frameworks: Current state and future challenges
Villar-Rodríguez, E., Arostegi, M., Torre-Bastida, A. I., Regueiro, C., & López-de-Armentia, J. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103278 · Cited by 38 · see citing works
Fog Intelligence for Secure Smart Villages: Architecture and Future Challenges
Aljuhani, A., Kumar, P., Kumar, R., Jolfaei, A., & Islam, A. K. M. N. (2022) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2022.3193268 · Cited by 36 · see citing works
“4 The main principle of fog computing is to extend the cloud closer to IoT devices, acting as an intermediate layer between the IoT end user and the cloud.”
BackgroundSwarm Intelligence-Based Task Scheduling for Enhancing Security for IoT Devices
Zhou, J., Shen, Y., Li, L., Zhuo, C., & Chen, M. (2022) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2022.3207328 · Cited by 36 · see citing works
“The consequence would be worse when devices in Industrial Internet of Things (IIoT) suffer security attacks since IIoT devices are mostly security-critical systems and have strict security requirements [3].”
Background
- Authors
- Tange, K., De Donno, M., Fafoutis, X., & Dragoni, N.
- Affiliations
- Technical University of Denmark (DK)
- Örebro University (SE)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2020
- Volume
- 22
- Issue
- 4
- Pages
- 2489-2520
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W3044855437
- Cited by
- 410
- References
- 251
- Citations by year
- 2026: 45 · 2025: 58 · 2024: 77 · 2023: 89 · 2022: 68 · 2021: 68 · 2020: 5
- FWCI
- 27.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion, cc-by)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, cc-by)
- Funders
- European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie (764785)
- FORA–Fog Computing for Robotics and Industrial Automation
- Poul V. Andersen Fund
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- Industrial Internet of Things, IIoT security, security requirements, fog computing, Industry 4.0, Internet of Things security, cyber-physical security, cloud computing, literature survey
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