Security and privacy in fog computing: Challenges
Open accessAbstract
Fog computing paradigm extends the storage, networking, and computing facilities of the cloud computing toward the edge of the networks while offloading the cloud data centers and reducing service latency to the end users. However, the characteristics of fog computing arise new security and privacy challenges. The existing security and privacy measurements for cloud computing cannot be directly applied to the fog computing due to its features, such as mobility, heterogeneity, and large-scale geo-distribution. This paper provides an overview of existing security and privacy concerns, particularly for the fog computing. Afterward, this survey highlights ongoing research effort, open challenges, and research trends in privacy and security issues for fog computing.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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 growing variety of 5G services leads to unprecedented levels of complexity in mobile resource management.
“The growing variety of 5G services leads to unprecedented levels of complexity in mobile resource management [175].”
From Blockchain for 5G and beyond networks: A state of the art survey (2020) · cites this paper as [175]
Cites
Edge computing: Vision and challenges
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2579198 · Cited by 8,733 · see citing works
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
Towards a Better Understanding of Context and Context-Awareness
Abowd, G. D., Dey, A. K., Brown, P. J., Davies, N., Smith, M. T., & Steggles, P. (1999) · Lecture notes in computer science · doi:10.1007/3-540-48157-5_29 · Cited by 2,994 · see citing works
Context Aware Computing for The Internet of Things: A Survey
Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.042313.00197 · Cited by 2,861 · cited 1× · see citing works
“As resources of EU’s devices are shared among other geographically close devices to support context-aware services [63], [64], location, massive amount data and other information of EU need to be protected in very secure manner.”
BackgroundFog and IoT: An Overview of Research Opportunities
Chiang, M., & Zhang, T. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2584538 · Cited by 2,362 · see citing works
Buyya, R., Yeo, C. S., & Venugopal, S. (2008) · Cited by 1,792 · see citing works
Yi, S., Li, C., & Li, Q. (2015) · doi:10.1145/2757384.2757397 · Cited by 1,358 · see citing works
A Taxonomy and Survey of Cloud Computing Systems
Rimal, B. P., Choi, E., & Lumb, L. I. (2009) · doi:10.1109/ncm.2009.218 · Cited by 1,322 · see citing works
Buyya, R., Yeo, C. S., & Venugopal, S. (2008) · IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc.2008.172 · Cited by 1,157 · see citing works
The Fog Computing Paradigm: Scenarios and Security Issues
Stojmenovic, I., & Wen, S. (2014) · Annals of Computer Science and Information Systems · doi:10.15439/2014f503 · Cited by 1,037 · see citing works
Fog Computing: A Taxonomy, Survey and Future Directions
Mahmud, R., Ramamohanarao, K., & Buyya, R. (2017) · Internet of things · doi:10.1007/978-981-10-5861-5_5 · Cited by 935 · see citing works
A survey of intrusion detection techniques in Cloud
Modi, C., Patel, D., Borisaniya, B., Patel, H. B., Patel, A., & Rajarajan, M. (2012) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2012.05.003 · Cited by 897 · see citing works
UAV-Based IoT Platform: A Crowd Surveillance Use Case
Motlagh, N. H., Bagaa, M., & Taleb, T. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600587cm · Cited by 753 · see citing works
Fog Computing for the Internet of Things: Security and Privacy Issues
Alrawais, A., Alhothaily, A., Hu, C., & Cheng, X. (2017) · IEEE Internet Computing · doi:10.1109/mic.2017.37 · Cited by 727 · see citing works
Fog-computing-based radio access networks: issues and challenges
Peng, M., Yan, S., Zhang, K., & Wang, C. (2016) · IEEE Network · doi:10.1109/mnet.2016.7513863 · Cited by 661 · see citing works
Assessment of the Suitability of Fog Computing in the Context of Internet of Things
Sarkar, S., Chatterjee, S., & Misra, S. (2018) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2015.2485206 · Cited by 638 · see citing works
Challenges and opportunities in edge computing
Varghese, B., Wang, N., Barbhuiya, S., Kilpatrick, P., & Nikolopoulos, D. S. (2016) · 2016 IEEE International Conference on Smart Cloud (SmartCloud) · doi:10.1109/smartcloud.2016.18 · Cited by 565 · see citing works
Security and Privacy Issues of Fog Computing: A Survey
Yi, S., Qin, Z., & Li, Q. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-21837-3_67 · Cited by 529 · see citing works
Toward intelligent machine-to-machine communications in smart grid
Fadlullah, Z. M., Fouda, M. M., Kato, N., Takeuchi, A., Iwasaki, N., & Nozaki, Y. (2011) · IEEE Communications Magazine · doi:10.1109/mcom.2011.5741147 · Cited by 518 · see citing works
A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing-Enhanced IoT
Lu, R., Heung, K., Lashkari, A. H., & Ghorbani, A. A. (2017) · IEEE Access · doi:10.1109/access.2017.2677520 · Cited by 478 · see citing works
TrustCloud: A Framework for Accountability and Trust in Cloud Computing
Ko, R. K. L., Jagadpramana, P., Mowbray, M., Pearson, S., Kirchberg, M., Liang, Q. A., & Lee, B. (2011) · IEEE World Congress on Services (SERVICES) · doi:10.1109/services.2011.91 · Cited by 412 · see citing works
Establishing Trust in Cloud Computing
Khan, K. M., & Malluhi, Q. M. (2010) · IT Professional · doi:10.1109/mitp.2010.128 · Cited by 358 · see citing works
Fog computing: A cloud to the ground support for smart things and machine-to-machine networks
Stojmenović, I. (2014) · International Telecommunication Networks and Applications Conference (ITNAC) · doi:10.1109/atnac.2014.7020884 · Cited by 306 · see citing works
Security, Privacy, and Fairness in Fog-Based Vehicular Crowdsensing
Ni, J., Zhang, A., Lin, X., & Shen, X. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600679 · Cited by 271 · see citing works
Basudan, S., Lin, X. S., & Sankaranarayanan, K. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2666783 · Cited by 265 · see citing works
Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud
Stolfo, S. J., Salem, M. B., & Keromytis, A. D. (2012) · doi:10.1109/spw.2012.19 · Cited by 251 · see citing works
Technical Issues of Forensic Investigations in Cloud Computing Environments
Birk, D., & Wegener, C. (2011) · doi:10.1109/sadfe.2011.17 · Cited by 216 · see citing works
Hu, P.-F., Ning, H., Qiu, T., Song, H., Wang, Y., & Yao, X. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2659783 · Cited by 216 · see citing works
Fog Computing: The Cloud-IoT\/IoE Middleware Paradigm
Aazam, M., & Huh, E. (2016) · IEEE Potentials · doi:10.1109/mpot.2015.2456213 · Cited by 207 · see citing works
Anwar, S., Zain, J. M., Zolkipli, M. F., Inayat, Z., Khan, S., Anthony, B., & Chang, V. I. C. (2017) · Algorithms · doi:10.3390/a10020039 · Cited by 190 · see citing works
Real-time intrusion detection in power system operations
Valenzuela, J. F., Wang, J., & Bissinger, N. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2224144 · Cited by 184 · see citing works
Cloud application logging for forensics
Marty, R. (2011) · ACM Symposium on Applied Computing · doi:10.1145/1982185.1982226 · Cited by 183 · see citing works
Lucy in the sky without diamonds: Stealing confidential data in the cloud
Rocha, F., & Correia, M. P. (2011) · IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W) · doi:10.1109/dsnw.2011.5958798 · Cited by 169 · see citing works
Secure intelligent traffic light control using fog computing
Liu, J., Li, J., Zhang, L., Dai, F., Zhang, Y., Meng, X., & Shen, J. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2017.02.017 · Cited by 168 · see citing works
Fog Computing: Issues and Challenges in Security and Forensics
Wang, Y., Uehara, T., & Sasaki, R. (2015) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac.2015.173 · Cited by 164 · see citing works
Anonymous and secure aggregation scheme in fog-based public cloud computing
Wang, H., Wang, Z., & Domingo‐Ferrer, J. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.02.032 · Cited by 162 · see citing works
A Cybersecurity Detection Framework for Supervisory Control and Data Acquisition Systems
Cruz, T., Rosa, L., Proença, J., Maglaras, L. A., Aubigny, M., Lev, L., Jiang, J., & Simões, P. (2016) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2016.2599841 · Cited by 150 · see citing works
Self-citationPrivate data deduplication protocols in cloud storage
Ng, W. K., Wen, Y., & Zhu, H. (2012) · ACM Symposium on Applied Computing · doi:10.1145/2245276.2245361 · Cited by 149 · see citing works
Octopus: An Edge-Fog Mutual Authentication Scheme
Ibrahim, M. H. (2016) · International journal of network security · doi:10.6633/ijns.201611.18(6).10 · Cited by 138 · see citing works
Privacy-Preserving Schemes for Ad Hoc Social Networks: A Survey
Ferrag, M. A., Maglaras, L. A., & Ahmim, A. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2718178 · Cited by 137 · see citing works
Self-citationCloud Computing: The impact on digital forensic investigations
Biggs, S., & Vidalis, S. (2009) · International Conference for Internet Technology and Secured Transactions · doi:10.1109/icitst.2009.5402561 · Cited by 134 · see citing works
Trends and challenges in cloud datacenters
Bilal, K., Malik, S. U. R., Khan, S. U., & Zomaya, A. Y. (2014) · IEEE Cloud Computing · doi:10.1109/mcc.2014.26 · Cited by 109 · see citing works
Efficient nonce-based authentication scheme for Session Initiation Protocol
Tsai, J. L. (2009) · doi:10.6633/ijns.200907.9(1).03 · Cited by 109 · see citing works
Cloud Forensics: A Meta-Study of Challenges, Approaches, and Open ProblemsPreprint
Zawoad, S., & Hasan, R. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1302.6312 · Cited by 105 · see citing works
Trajectory Privacy Preservation Based on a Fog Structure for Cloud Location Services
Wang, T., Zeng, J., Bhuiyan, M. Z. A., Tian, H., Cai, Y., Chen, Y., & Zhong, B. (2017) · IEEE Access · doi:10.1109/access.2017.2698078 · Cited by 97 · see citing works
Koo, D., & Hur, J. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.01.024 · Cited by 95 · see citing works
Maglaras, L. A., Jiang, J., & Cruz, T. (2016) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2016.04.002 · Cited by 82 · see citing works
Self-citationWAKE: Key management scheme for wide-area measurement systems in smart grid
Law, Y. W., Palaniswami, M. S., Kounga, G., et al. (2013) · IEEE Communications Magazine · doi:10.1109/mcom.2013.6400436 · Cited by 71 · see citing works
Front-end intelligence for large-scale application-oriented internet-of-things
Bader, A., Ghazzai, H., Kadri, A., & Alouini, M. (2016) · IEEE Access · doi:10.1109/access.2016.2580623 · Cited by 68 · see citing works
A Differential Privacy-Based Query Model for Sustainable Fog Data Centers
Du, M., Wang, K., Liu, X., et al. (2017) · IEEE Transactions on Sustainable Computing · doi:10.1109/tsusc.2017.2715038 · Cited by 64 · see citing works
Privacy Preserving Smart Meter Streaming Against Information Leakage of Appliance Status
Hong, Y., Liu, W. M., & Wang, L. (2017) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2017.2704904 · Cited by 63 · see citing works
Position based cryptography with location privacy: A step for Fog Computing
Yang, R., Xu, Q., Au, M. H., Yu, Z., Wang, H., & Zhou, L. Q. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.05.035 · Cited by 62 · see citing works
Overcast: Forensic Discovery in Cloud Environments
Wolthusen, S. D. B. (2009) · doi:10.1109/imf.2009.21 · Cited by 61 · see citing works
Isolating a cloud instance for a digital forensic investigation.
Delport, W., Köhn, M., & Olivier, M. S. (2011) · Cited by 58 · see citing works
Fog computing: Common security issues and proposed countermeasures
Kumar, P., Zaidi, N., & Choudhury, T. (2016) · doi:10.1109/sysmart.2016.7894541 · Cited by 52 · see citing works
Guessing Attacks on Strong-Password Authentication Protocol
Lee, C., Liu, C.-H., & Hwang, M. (2013) · Cited by 47 · see citing works
LoDPD: A Location Difference-Based Proximity Detection Protocol for Fog Computing
Huo, Y., Hu, C., Qi, X., & Jing, T. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2670570 · Cited by 37 · see citing works
A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment
Xiao, M., Zhou, J., Liu, X., & Jiang, M. (2017) · Sensors · doi:10.3390/s17061423 · Cited by 37 · see citing works
An Enhanced Remote User Authentication Scheme with Smart Card
Kumar, M. (2010) · doi:10.6633/ijns.201005.10(3).02 · Cited by 32 · see citing works
A Simple User Authentication Scheme for Grid Computing
Lu, R., Cao, Z., Chai, Z., et al. (2008) · doi:10.6633/ijns.200809.7(2).08 · Cited by 30 · see citing works
Private proximity detection for convex polygons
Mu, B., & Bakiras, S. (2016) · Tsinghua Science & Technology · doi:10.1109/tst.2016.7488738 · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Li, Q., Wen, Z., Wu, Z., Hu, S., Wang, N., Li, Y., Liu, X., & He, B. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2021.3124599 · Cited by 1,407 · see citing works
Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues and Challenges
Yang, R., Yu, F. R., Si, P., Yang, Z., & Zhang, Y. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2894727 · Cited by 688 · see citing works
Blockchain for 5G and beyond networks: A state of the art survey
Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102693 · Cited by 412 · see citing works
Ahmad, S., Shakeel, I., Mehfuz, S., & Ahmad, J. (2023) · Computer Science Review · doi:10.1016/j.cosrev.2023.100568 · Cited by 197 · see citing works
Toward Secure and Trustworthy Vehicular Fog Computing: A Survey
Nazih, O., Benamar, N., Lamaazi, H., & Chaoui, H. (2024) · IEEE Access · doi:10.1109/access.2024.3371488 · Cited by 35 · see citing works
Journey from cloud of things to fog of things: survey, new trends, and research directions
Chakraborty, A., Kumar, M., Chaurasia, N., & Gill, S. S. (2023) · Software: Practice and Experience · doi:10.1002/spe.3157 · Cited by 31 · see citing works
- Authors
- Mukherjee, M., Matam, R., Shu, L., Maglaras, L., Ferrag, M. A., Choudhury, N., & Kumar, V.
- Affiliations
- Guangdong University of Petrochemical Technology (CN)
- De Montfort University (GB)
- Badji Mokhtar-Annaba University (DZ)
- ORCID
- Venue
- IEEE Access
- Published
- 2017
- Volume
- 5
- Pages
- 19293-19304
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2753672491
- Cited by
- 533
- References
- 61
- Citations by year
- 2026: 5 · 2025: 26 · 2024: 41 · 2023: 47 · 2022: 73 · 2021: 85 · 2020: 119 · 2019: 77 · 2018: 58 · 2017: 2
- FWCI
- 46.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DMU Open Research Archive (De Montfort University) (submittedVersion)
- Funders
- Maoming Engineering Research Center of Industrial Internet of Things (517018)
- National Natural Science Foundation of China (61401107)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- fog computing, security (computing), privacy, edge computing, cloud computing, latency reduction, mobility, heterogeneity, privacy-preserving computation
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