A blockchain future for internet of things security: a position paper
Open accessAbstract
Internet of Things (IoT) devices are increasingly being found in civilian and military contexts, ranging from smart cities and smart grids to Internet-of-Medical-Things, Internet-of-Vehicles, Internet-of-Military-Things, Internet-of-Battlefield-Things, etc. In this paper, we survey articles presenting IoT security solutions published in English since January 2016. We make a number of observations, including the lack of publicly available IoT datasets that can be used by the research and practitioner communities. Given the potentially sensitive nature of IoT datasets, there is a need to develop a standard for sharing IoT datasets among the research and practitioner communities and other relevant stakeholders. Thus, we posit the potential for blockchain technology in facilitating secure sharing of IoT datasets (e.g., using blockchain to ensure the integrity of shared datasets) and securing IoT systems, before presenting two conceptual blockchain-based approaches. We then conclude this paper with nine potential research questions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The green cluster groups authors studying the potentials of blockchain for securing the security and privacy of IoT transactions and information sharing.
“The green cluster groups all authors belonging to the same area of research and studying the potentials of blockchain for securing the security and privacy of IoT transactions and information sharing (Banerjee et al. 2018; Khan and Salah 2018; Makhdoom et al. 2020; Xu et al. 2018).”
From Blockchain technology in the smart city: A bibliometric review (2022) · cites this paper as Banerjee et al. 2018
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Blockchains and smart contracts for the internet of things
Christidis, K., & Devetsikiotis, M. (2016) · IEEE Access · doi:10.1109/access.2016.2566339 · Cited by 4,552 · see citing works
MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention
Saracino, A., Sgandurra, D., Dini, G., et al. (2016) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2016.2536605 · Cited by 435 · see citing works
2015 IEEE Global Communications Conference (GLOBECOM)
(2015) · doi:10.1109/globecom30361.2015 · Cited by 425 · see citing works
Stochastic Activity Networks: Formal Definitions and Concepts⋆
Sanders, W. H., & Meyer, J. F. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44667-2_9 · Cited by 336 · see citing works
Osanaiye, O. A., Choo, K. R., & Dlodlo, M. E. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.01.001 · Cited by 321 · see citing works
Self-citationTowards Achieving Data Security with the Cloud Computing Adoption Framework
Chang, V. I. C., & Ramachandran, M. (2015) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2015.2491281 · Cited by 291 · see citing works
Wagner, C., Dulaunoy, A., Wagener, G., & Iklody, A. (2016) · doi:10.1145/2994539.2994542 · Cited by 233 · see citing works
An Evaluation Framework for Intrusion Detection Dataset
Gharib, A., Sharafaldin, I., Lashkari, A. H., et al. (2016) · International Conferences on Information Science and System · doi:10.1109/icissec.2016.7885840 · Cited by 224 · see citing works
2015 IEEE Trustcom/BigDataSE/ISPA
(2015) · doi:10.1109/trustcom/bigdatase/i36604.2015 · Cited by 213 · see citing works
Mobile Health (m-Health) System in the Context of IoT
Almotiri, S. H., Khan, M. A., & Ghamdi, M. A. A. (2016) · doi:10.1109/w-ficloud.2016.24 · Cited by 205 · see citing works
2016 IEEE Symposium on Computers and Communication (ISCC)
(2016) · doi:10.1109/iscc38395.2016 · Cited by 161 · see citing works
Big Data Analysis-Based Security Situational Awareness for Smart Grid
Wu, J., Ota, K., Dong, M., Li, J., & Wang, H. (2018) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2016.2616146 · Cited by 144 · cited 1× · see citing works
“[71] described a security situational awareness mechanism based on the analysis of big da ta for smart grids.”
MethodLi, B., Lu, R., Wang, W., & Choo, K. R. (2016) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2016.12.012 · Cited by 138 · see citing works
Self-citationPrivacy Protection and Intrusion Avoidance for Cloudlet-Based Medical Data Sharing
Chen, M., Qian, Y., Chen, J., Hwang, K., Mao, S., & Hu, L. (2016) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2016.2617382 · Cited by 111 · see citing works
Performance Comparison and Detection Analysis in Snort and Suricata Environment
Park, W., & Ahn, S. (2016) · Wireless Personal Communications · doi:10.1007/s11277-016-3209-9 · Cited by 98 · see citing works
2016 24th Iranian Conference on Electrical Engineering (ICEE)
(2016) · doi:10.1109/icee38180.2016 · Cited by 88 · see citing works
The Common Vulnerability Scoring System (CVSS)
Ou, X., & Singhal, A. (2011) · SpringerBriefs in computer science · doi:10.1007/978-1-4614-1860-3_3 · Cited by 86 · see citing works
Intrusion Detection and Prevention for ZigBee-Based Home Area Networks in Smart Grids
Jokar, P., & Leung, V. C. M. (2016) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2600585 · Cited by 86 · see citing works
2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC)
(2015) · doi:10.1109/dasc34242.2015 · Cited by 80 · see citing works
MILCOM 2016 - 2016 IEEE Military Communications Conference
(2016) · doi:10.1109/milcom39005.2016 · Cited by 70 · see citing works
(2012) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2012.2190919 · Cited by 64 · see citing works
How to Detect Cyber-Attacks in Unmanned Aerial Vehicles Network?
Sedjelmaci, H., Senouci, S., & Messous, M.-A. (2016) · Globecom · doi:10.1109/glocom.2016.7841878 · Cited by 63 · see citing works
Collaborative network security in multi-tenant data center for cloud computing
Chen, Z., Dong, W., Li, H., et al. (2014) · Tsinghua Science & Technology · doi:10.1109/tst.2014.6733211 · Cited by 62 · see citing works
Network malware classification comparison using DPI and flow packet headers
Boukhtouta, A., Mokhov, S. A., Lakhdari, N.-E., Debbabi, M., & Paquet, J. (2015) · Journal of Computer Virology and Hacking Techniques · doi:10.1007/s11416-015-0247-x · Cited by 60 · see citing works
Cloudlet Mesh for Securing Mobile Clouds from Intrusions and Network Attacks
Shi, Y., Abhilash, S., & Hwang, K. (2015) · IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) · doi:10.1109/mobilecloud.2015.15 · Cited by 53 · see citing works
Shaghaghi, A., Kâafar, M. A., & Jha, S. K. (2017) · ACM Asia Conference on Computer and Communications Security (ASIA CCS) · doi:10.1145/3052973.3053039 · Cited by 49 · see citing works
Indre, I., & Lemnaru, C. (2016) · IEEE International Conference on Intelligent Computer Communication and Processing (ICCP) · doi:10.1109/iccp.2016.7737142 · Cited by 43 · see citing works
2016 8th International Symposium on Telecommunications (IST)
(2016) · doi:10.1109/ist39834.2016 · Cited by 42 · see citing works
Intrusion prevention system of automotive network CAN bus
Abbott-McCune, S., & Shay, L. A. (2016) · IEEE International Carnahan Conference on Security Technology (ICCST) · doi:10.1109/ccst.2016.7815711 · Cited by 40 · see citing works
Arya, N., Singh, U., & Singh, S. (2015) · International Conference on Computer, Communication and Control · doi:10.1109/ic4.2015.7375649 · Cited by 39 · see citing works
2015 44th International Conference on Parallel Processing
(2015) · doi:10.1109/icpp37153.2015 · Cited by 35 · see citing works
Cloud security and privacy model for providing secure cloud services
Makkaoui, K. E., Ezzati, A., Beni‐Hssane, A., et al. (2016) · doi:10.1109/cloudtech.2016.7847682 · Cited by 34 · see citing works
2018 19th International Carpathian Control Conference (ICCC)
(2018) · doi:10.1109/iccc43746.2018 · Cited by 34 · see citing works
Secure data transmission on MANET by hybrid cryptography technique
Sharma, A. K., Bhuriya, D., & Singh, U. (2015) · International Conference on Computer, Communication and Control · doi:10.1109/ic4.2015.7375688 · Cited by 31 · see citing works
ANSwer: Combining NFV and SDN features for network resilience strategies
Machado, C. C., Granville, L. Z., & Schaeffer-Filho, A. E. (2016) · doi:10.1109/iscc.2016.7543771 · Cited by 28 · see citing works
Mirza, N. A. S., Abbas, H., Khan, F. A., et al. (2014) · International Symposium on Biometrics and Security Technologies · doi:10.1109/isbast.2014.7013108 · Cited by 27 · see citing works
Detection as a service: An SDN application
Monshizadeh, M., Khatri, V., & Kantola, R. (2017) · International Conference on Advanced Communication Technology · doi:10.23919/icact.2017.7890099 · Cited by 26 · see citing works
Community-Based Secure Information and Resource Sharing in AWS Public Cloud
Zhang, Y., Patwa, F., & Sandhu, R. S. (2015) · doi:10.1109/cic.2015.42 · Cited by 24 · see citing works
IEEE Transactions on Cloud Computing
(2012) · IEEE Transactions on Network and Service Management · doi:10.1109/twc.2011.09.2785-515-tnsm1212-cloudcomputing · Cited by 24 · see citing works
SkipMon: A locality-aware Collaborative Intrusion Detection System
Vasilomanolakis, E., Krugl, M., Cordero, C. G., et al. (2015) · IEEE International Performance, Computing, and Communications Conference · doi:10.1109/pccc.2015.7410282 · Cited by 23 · see citing works
The Performance Analysis of Honeypot Based Intrusion Detection System for Wireless Network
Agrawal, N., & Tapaswi, S. (2017) · International Journal of Wireless Information Networks · doi:10.1007/s10776-016-0330-3 · Cited by 22 · see citing works
Proceedings of the International Congress on Information and Communication Technology
Mishra, D. K., Joshi, A., Bhatt, Y. C., et al. (2016) · Advances in intelligent systems and computing · doi:10.1007/978-981-10-0755-2 · Cited by 22 · see citing works
A Novel Adaptive Grey Verhulst Model for Network Security Situation Prediction
Leau, Y., & Manickam, S. (2016) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2016.070113 · Cited by 20 · see citing works
Intent-Based Extensible Real-Time PHP Supervision Framework
Prokhorenko, V., Choo, K. R., & Ashman, H. (2016) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2016.2569063 · Cited by 20 · see citing works
Self-citationA Framework for Security Enhancement in SDN-Based Datacenters
Moustafa, A., Rizk, M. R. M., Abdel-Hamid, A., et al. (2016) · IFIP International Conference on New Technologies, Mobility and Security (NTMS) · doi:10.1109/ntms.2016.7792427 · Cited by 20 · see citing works
Privacy Preserving Data Quality Assessment for High-Fidelity Data Sharing
Freudiger, J., Rane, S. D., Brito, A. E., & Uzun, E. (2014) · doi:10.1145/2663876.2663885 · Cited by 19 · see citing works
Internet of things network management system architecture for smart healthcare
Sallabi, F., & Shuaib, K. (2016) · International Conference on Digital Information and Communication Technology and its Applications (DICTAP) · doi:10.1109/dictap.2016.7544021 · Cited by 19 · see citing works
An Analysis of CVSS v2 Environmental Scoring
Ibidapo, A. O., Zavarsky, P., Lindskog, D., et al. (2011) · doi:10.1109/passat/socialcom.2011.121 · Cited by 19 · see citing works
The security of RFID readers with IDS/IPS solution using Raspberry Pi
Zitta, T., Neruda, M., & Vojtěch, L. (2017) · International Carpathian Control Conference · doi:10.1109/carpathiancc.2017.7970418 · Cited by 19 · see citing works
2014 22nd Telecommunications Forum Telfor (TELFOR)
(2014) · doi:10.1109/telfor34903.2014 · Cited by 19 · see citing works
Coping with denial-of-service attacks on the IP telephony system
Cadet, F., & Fokum, D. T. (2016) · Proceedings of IEEE Southeastcon · doi:10.1109/secon.2016.7506691 · Cited by 18 · see citing works
Olagunju, A. O., & Samu, F. (2016) · doi:10.1145/2978178.2978184 · Cited by 18 · see citing works
Ford, M., Mallery, C., Palmasani, F., et al. (2016) · Proceedings of IEEE Southeastcon · doi:10.1109/secon.2016.7506771 · Cited by 16 · see citing works
Yacchirena, A., Alulema, D., Aguilar, D., et al. (2016) · doi:10.1109/ica-acca.2016.7778423 · Cited by 16 · see citing works
A Novel Architecture for Predictive CyberSecurity Using Non-homogenous Markov Models
Abraham, S., & Nair, S. (2015) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications / BigDataSE / ISPA (Trustcom/BigDataSE/ISPA) · doi:10.1109/trustcom.2015.446 · Cited by 15 · see citing works
Performance Study of 802.11w for Preventing DoS Attacks on Wireless Local Area Networks
Liu, C., & Qiu, J. (2016) · Wireless Personal Communications · doi:10.1007/s11277-016-3812-9 · Cited by 15 · see citing works
CYSM: An Innovative Physical/Cyber Security Management System for Ports
Papastergiou, S., Polemi, N., & Karantjias, A. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-20376-8_20 · Cited by 14 · see citing works
Requirements-driven mediation for collaborative security
Bennaceur, A., Bandara, A. K., Jackson, M., et al. (2014) · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) · doi:10.1145/2593929.2593938 · Cited by 14 · see citing works
Controlled Data Sharing for Collaborative Predictive BlacklistingPreprint
Freudiger, J., Cristofaro, E. D., & Brito, A. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.05337 · Cited by 14 · see citing works
Pattern matching intrusion detection technique for Wireless Sensor Networks
Kalnoor, G., & Agarkhed, J. V. (2016) · International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics · doi:10.1109/aeeicb.2016.7538389 · Cited by 13 · see citing works
Enhancement of VPN Authentication Using GPS Information with Geo-Privacy Protection
Jin, Y., Tomoishi, M., & Matsuura, S. (2016) · International Conference on Computer Communication and Networks (ICCCN) · doi:10.1109/icccn.2016.7568518 · Cited by 13 · see citing works
An FPGA Architecture for ASIC-FPGA Co-design to Streamline Processing of IDSs
Sato, T., Chivapreecha, S., Moungnoul, P., et al. (2016) · International Conference on Collaboration Technologies and Systems (CTS) · doi:10.1109/cts.2016.0079 · Cited by 13 · see citing works
Pan, X., Yegneswaran, V., Chen, Y., et al. (2016) · doi:10.1145/2876019.2876023 · Cited by 12 · see citing works
A General Collaborative Framework for Modeling and Perceiving Distributed Network Behavior
Xie, Y., Wang, Y., He, H., et al. (2016) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2015.2512609 · Cited by 12 · see citing works
Implementing Intrusion Management as Security-as-a-service from cloud
Sharma, D. H., Dhote, C. A., & Potey, M. M. (2016) · International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS) · doi:10.1109/csitss.2016.7779387 · Cited by 12 · see citing works
DoS attacks prevention using IDS and data mining
Keshri, A., Singh, S., Agarwal, M., et al. (2016) · doi:10.1109/icadw.2016.7942518 · Cited by 11 · see citing works
A network defense system for detecting and preventing potential hacking attempts
Alsunbul, S., Le, P. D., Tan, J., et al. (2016) · International Conference on Information Networking · doi:10.1109/icoin.2016.7427157 · Cited by 10 · see citing works
A Cloud-Based Energy Efficient System for Enhancing the Detection and Prevention of Modern Malware
Mirza, Q. K. A., Mohi-ud-din, G., & Awan, I. U. (2016) · IEEE International Conference on Advanced Information Networking and Applications (AINA) · doi:10.1109/aina.2016.133 · Cited by 10 · see citing works
Swapna, A. I., Rahman, Z., Rahman, M. H., et al. (2016) · doi:10.1109/cci.2016.7778919 · Cited by 10 · see citing works
Multi-level Intrusion detection system in cloud environment based on trust level
Salek, Z., & Madani, F. M. (2016) · International Conference on Computer and Knowledge Engineering · doi:10.1109/iccke.2016.7802122 · Cited by 10 · see citing works
Securing Mobile Ad Hoc Networks using distributed firewall with PKI
Filipek, J., & Hudec, L. (2016) · IEEE International Symposium on Applied Machine Intelligence and Informatics (SAMI) · doi:10.1109/sami.2016.7423028 · Cited by 9 · see citing works
Community-Based Collaborative Intrusion Detection
Cordero, C. G., Vasilomanolakis, E., Mühlhäuser, M., & Fischer, M. (2015) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-319-28865-9_44 · Cited by 9 · see citing works
Attack detection of distributed denial of service based on Splunk
Su, T., Wang, S., Chen, Y.-F., et al. (2016) · doi:10.1109/icamse.2016.7840355 · Cited by 9 · see citing works
Game-theoretic strategies for IDS deployment in peer-to-peer networks
Narang, P., & Hota, C. (2015) · Information Systems Frontiers · doi:10.1007/s10796-015-9582-1 · Cited by 8 · see citing works
Advanced security management system for critical infrastructures
Karantjias, A., Polemi, N., & Papastergiou, S. (2014) · doi:10.1109/iisa.2014.6878837 · Cited by 8 · see citing works
Enhancing Access-Control with Risk-Metrics for Collaboration on Social Cloud-Platforms
Bouchami, A., Goettelmann, E., Perrin, O., et al. (2015) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications / BigDataSE / ISPA (Trustcom/BigDataSE/ISPA) · doi:10.1109/trustcom.2015.458 · Cited by 8 · see citing works
DISCS: A DIStributed Collaboration System for Inter-AS Spoofing Defense
Liu, B., & Bi, J. (2015) · Proceedings of the International Conference on Parallel Processing · doi:10.1109/icpp.2015.25 · Cited by 8 · see citing works
“I know what you did before”: General framework for correlation analysis of cyber threat incidents
Kim, D., Woo, J., & Kim, H. K. (2016) · IEEE Military Communications Conference (MILCOM) · doi:10.1109/milcom.2016.7795424 · Cited by 8 · see citing works
Wilson, J., Brown, J. M., & Biddle, R. (2014) · doi:10.1145/2663887.2663902 · Cited by 7 · see citing works
Hiran, R., Carlsson, N. F., & Shahmehri, N. (2014) · doi:10.1145/2663876.2663879 · Cited by 6 · see citing works
Collaborative intrusion detection as a service in cloud computing environment
Hong, L., Ge, Y., Wang, W., et al. (2015) · IEEE International Conference on Progress in Informatics and Computing · doi:10.1109/pic.2015.7489893 · Cited by 6 · see citing works
Configuration strategies for collaborative IDS using game theory
Ghorbani, M., Ghorbani, H. R., & Hashemi, M. R. (2016) · Iranian Conference on Electrical Engineering · doi:10.1109/iraniancee.2016.7585529 · Cited by 6 · see citing works
A performance study of anomaly detection using entropy method
Waskita, A. A., Suhartanto, H. S., & Handoko, L. T. (2016) · International Conference on Computer, Control, Informatics and its Applications · doi:10.1109/ic3ina.2016.7863038 · Cited by 6 · see citing works
Accounting for the Human User in Predictive Security Models
Noureddine, M. A., Marturano, A., Keefe, K., Bashir, M. N., & Sanders, W. H. (2017) · IEEE Pacific Rim International Symposium on Dependable Computing (PRDC) · doi:10.1109/prdc.2017.58 · Cited by 6 · see citing works
LESS Is More: Host-Agent Based Simulator for Large-Scale Evaluation of Security Systems
Sonchack, J., & Aviv, A. J. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11212-1_21 · Cited by 5 · see citing works
Security situation management developing a concept of operations and threat prediction capability
Kolev, D., Koelle, R., Rodriguez, R. A. C., & Montefusco, P. (2015) · IEEE/AIAA Digital Avionics Systems Conference (DASC) · doi:10.1109/dasc.2015.7311586 · Cited by 5 · see citing works
A crowdsourcing approach to protect against novel malware threats
Christoforidis, C., Vlachos, V., & Androulidakis, I. I. (2014) · Telecommunications Forum Telfor (TELFOR) · doi:10.1109/telfor.2014.7034590 · Cited by 5 · see citing works
ASIC design and implementation for VoIP intrusion prevention system
Chen, M., Wen, C., Lin, H.-C., et al. (2016) · International Conference on Applied System Innovation · doi:10.1109/icasi.2016.7539941 · Cited by 5 · see citing works
Intelligent intrusion prevention system for households based on system-on-chip computer
Rashid, M. T., Abir, I. K., Shourove, N. S., et al. (2016) · IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) · doi:10.1109/ccece.2016.7726816 · Cited by 5 · see citing works
Quality evidence, quality decisions: Ways to improve security and privacy of EHR systems
Osop, H., & Sahama, T. R. (2016) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2016.7749424 · Cited by 5 · see citing works
Optimal response to computer network threats
Abazari, F., Madani, A., & Gharaee, H. (2016) · International Symposium on Telecommunications · doi:10.1109/istel.2016.7881919 · Cited by 5 · see citing works
OpenAppID - application identification framework next generation of firewalls
Patel, N. V., Patel, N. M., & Kleopa, C. (2016) · Online International Conference on Green Engineering and Technologies · doi:10.1109/get.2016.7916721 · Cited by 5 · see citing works
Saied, Y. B., Olivereau, A., Zeghlache, D., et al. (2014) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2014.07.036 · Cited by 4 · see citing works
Intrusion detection and prevention system using K-learning classification in cloud
Kumawat, S., Sharma, A., & Kumawat, A. (2016) · International Conference on Computing for Sustainable Global Development · Cited by 4 · see citing works
Intrusion Filtration System(IFS)-mapping network security in new way
Dewanjee, R. (2016) · International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES) · doi:10.1109/scopes.2016.7955883 · Cited by 4 · see citing works
An Architecture for Self-adaptive Distributed Firewall
Júnior, E. P. D. C., Medeiros, S. T., da Silva, C. E., et al. (2016) · doi:10.5753/sbseg.2016.19318 · Cited by 4 · see citing works
WedgeTail: An Intrusion Prevention System for the Data Plane of Software Defined Networks
Shaghaghi, A., Kaafar, M. A., & Jha, S. (2017) · Figshare · doi:10.48550/arxiv.1708.05477 · Cited by 4 · see citing works
GAMMA - Filling the security management void of SESAR and NextGen
Koelle, R., Markarian, G., & Kolev, D. (2014) · doi:10.1109/icnsurv.2014.6819992 · Cited by 3 · see citing works
Balancing Delays and Energy Consumption in IPS-Enabled Networks
Merlo, A., Migliardi, M., & Spadacini, E. (2016) · International Conference on Advanced Information Networking and Applications Workshops (WAINA) · doi:10.1109/waina.2016.109 · Cited by 3 · see citing works
Mitigation Techniques for Gray Hole and Black Hole Attacks in Wireless Mesh Network
Rathee, G., & Saini, H. (2016) · Advances in intelligent systems and computing · doi:10.1007/978-981-10-0755-2_41 · Cited by 3 · see citing works
Detecting Intrusions in Federated Cloud Environments Using Security as a Service
MacDermott, Á., Shi, Q., & Kifayat, K. (2015) · doi:10.1109/dese.2015.28 · Cited by 3 · see citing works
Collaborative Incident Handling Based on the Blackboard-Pattern
Herold, N., Kinkelin, H., & Carle, G. (2016) · doi:10.1145/2994539.2994545 · Cited by 3 · see citing works
Smartphone nabbing: Analysis of intrusion detection and prevention systems
Vij, S., & Jain, A. (2016) · Cited by 3 · see citing works
Protection of shared data among multiple users for online social networks
Ganesh, D., & RamaPrasad, V. V. (2014) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i.2014.7019682 · Cited by 3 · see citing works
An adaptive algorithm for detecting and preventing attacks in telecommunication networks
Yevdokymenko, M. (2016) · International Scientific-Practical Conference Problems of Infocommunications Science and Technology · doi:10.1109/infocommst.2016.7905373 · Cited by 3 · see citing works
Securely detecting an intruders in MANETs system
Indumathi, G., & Sakthivel, S. (2014) · International Conference on Information Communication and Embedded Systems · doi:10.1109/icices.2014.7033773 · Cited by 2 · see citing works
Fine-Grained Risk Level Quantication Schemes Based on APK Metadata
Takahashi, T., Ban, T., Mimura, T., et al. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-26555-1_75 · Cited by 2 · see citing works
Artifical immune system using Genetic Algorithm and decision tree
Al-Douri, Y. K., Pangracious, V., & Al-Doori, M. (2016) · International Conference on Bio-engineering for Smart Technologies (BioSMART) · doi:10.1109/biosmart.2016.7835603 · Cited by 2 · see citing works
A large-scale URL filtering algorithm in high-speed flow
Qinglin, H., & Ma, X. (2016) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/compcomm.2016.7924863 · Cited by 2 · see citing works
Advances In Distributed Security For Mobile Ad Hoc Networks
Filipek, J., & Hudec, L. (2016) · International Conference on Computer Systems and Technologies (CompSysTech) · doi:10.1145/2983468.2983480 · Cited by 1 · see citing works
Design and Implementation of an Intrusion Prevention System Inspired Immune Systems.
Farhaoui, Y. (2017) · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- Rahul Hiran, Niklas Carlsson, Nahid Shahmehri, PrefiSec: a distributed alliance framework for collaborative BGP monitoring and prefix-based security, in: Proceedings of the 2014 ACM Workshop on Information Sharing & Collaborative Security (WISCS '14), ACM, New York, NY, USA, 2014, pp. 3-12.
- Xiang Pan, Vinod Yegneswaran, Yan Chen, Phillip Porras, Seungwon Shin, HogMap: using SDNs to incentivize collaborative security monitoring, in: Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization (SDN-NFV Security '16), ACM, New York, NY, USA, 2016, pp. 7-12.
- K. Hwang, D. Li, Trusted cloud computing resources and data coloring, IEEE Internet Co. 14 (Sept. 2010).
Cited by
Sorted by citations
On blockchain and its integration with IoT. Challenges and opportunities
Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.05.046 · Cited by 1,908 · see citing works
Blockchain for internet of things: a survey
Dai, H.-N., Zheng, Z., & Zhang, Y. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2920987 · Cited by 1,246 · see citing works
A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues
Stoyanova, M., Nikoloudakis, Y., Panagiotakis, S., Pallis, E., & Markakis, E. K. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2962586 · Cited by 852 · see citing works
Mistry, I., Tanwar, S., Tyagi, S., & Kumar, N. (2020) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2019.106382 · Cited by 585 · see citing works
Blockchain Technology in Healthcare: A Comprehensive Review and Directions for Future Research
Khezr, S., Moniruzzaman, M., Yassine, A., & Benlamri, R. (2019) · Applied Sciences · doi:10.3390/app9091736 · Cited by 575 · see citing works
Differential Privacy Techniques for Cyber Physical Systems: A Survey
Hassan, M. U., Rehmani, M. H., & Chen, J. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2944748 · Cited by 564 · see citing works
An exhaustive survey on security and privacy issues in Healthcare 4.0
Hathaliya, J. J., & Tanwar, S. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.02.018 · Cited by 462 · see citing works
Blockchain for smart communities: applications, challenges and opportunities
Aggarwal, S., Chaudhary, R., Aujla, G. S., Kumar, N., Choo, K.-K. R., & Zomaya, A. Y. (2019) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.06.018 · Cited by 344 · see citing works
Self-citationBest: blockchain-based secure energy trading in SDN enabled intelligent transportation system
Chaudhary, R., Jindal, A., Aujla, G. S., Aggarwal, S., Kumar, N., & Choo, K.-K. R. (2019) · Computers & Security · doi:10.1016/j.cose.2019.05.006 · Cited by 276 · see citing works
Self-citationBlockchain envisioned uav networks: challenges, solutions, and comparisons
Mehta, P., Gupta, R., & Tanwar, S. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.01.023 · Cited by 266 · see citing works
A Review of Blockchain-Based Systems in Transportation
Astarita, V., Giofrè, V. P., Mirabelli, G., & Solina, V. (2019) · Information · doi:10.3390/info11010021 · Cited by 180 · see citing works
Kumar, R., & Tripathi, R. (2021) · The Journal of Supercomputing · doi:10.1007/s11227-020-03570-x · Cited by 177 · see citing works
A Review of Blockchain in Internet of Things and AI
Atlam, H. F., Azad, M. A., Alzahrani, A. G., & Wills, G. (2020) · Big Data and Cognitive Computing · doi:10.3390/bdcc4040028 · Cited by 169 · see citing works
Kandasamy, K., Srinivas, S., Achuthan, K., & Rangan, V. P. (2020) · EURASIP Journal on Information Security · doi:10.1186/s13635-020-00111-0 · Cited by 160 · see citing works
Blockchain technology in the smart city: A bibliometric review
Rejeb, A., Rejeb, K., Simske, S. J., & Keogh, J. G. (2022) · Quality & Quantity · doi:10.1007/s11135-021-01251-2 · Cited by 104 · see citing works
Bads: blockchain-based architecture for data sharing with abs and cp-abe in IoT
Zhang, Y., He, D., & Choo, K.-K. R. (2018) · Wireless Communications and Mobile Computing · doi:10.1155/2018/2783658 · Cited by 102 · see citing works
Self-citationInternet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research
Wazzan, M., Algazzawi, D., Bamasaq, O., Albeshri, A., & Cheng, L. (2021) · Applied Sciences · doi:10.3390/app11125713 · Cited by 102 · see citing works
A unified framework for data integrity protection in people-centric smart cities
Altulyan, M., Yao, L., Kanhere, S. S., Wang, X., & Huang, C. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-019-7182-7 · Cited by 37 · see citing works
- Authors
- Banerjee, M., Lee, J., & Choo, K.-K. R.
- Affiliations
- The University of Texas at San Antonio (US)
- Corresponding author
- Choo, Kim-Kwang Raymond
- Venue
- Digital Communications and Networks
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 4
- Issue
- 3
- Pages
- 149-160
- ISSN
- 2352-8648 (ISSN-L)
- OpenAlex
- W2765928069
- Cited by
- 585
- References
- 154
- Citations by year
- 2026: 9 · 2025: 32 · 2024: 66 · 2023: 76 · 2022: 99 · 2021: 97 · 2020: 92 · 2019: 83 · 2018: 30 · 2017: 1
- FWCI
- 105.06
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Digital Communications and Networks (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- Internet of Things security, blockchain, IoT datasets, data sharing, data integrity, smart cities, Internet of Medical Things, smart grid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review