Survey on Multi-Access Edge Computing Security and Privacy
Open accessAbstract
The European Telecommunications Standards Institute (ETSI) has introduced the paradigm of Multi-Access Edge Computing (MEC) to enable efficient and fast data processing in mobile networks. Among other technological requirements, security and privacy are significant factors in the realization of MEC deployments. In this paper, we analyse the security and privacy of the MEC system. We introduce a thorough investigation of the identification and the analysis of threat vectors in the ETSI standardized MEC architecture. Furthermore, we analyse the vulnerabilities leading to the identified threat vectors and propose potential security solutions to overcome these vulnerabilities. The privacy issues of MEC are also highlighted, and clear objectives for preserving privacy are defined. Finally, we present future directives to enhance the security and privacy of MEC services.
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EC retains training data in edge device nodes to avoid the risk of privacy data leakages to a certain extent.
“The bottleneck in the transmission communication retains the training data in edge device nodes to avoid the risk of privacy data leakages to a certain extent (Li et al. 2022a;Ranaweera et al. 2021).”
From Survey: federated learning data security and privacy-preserving in edge-Internet of Things (2024) · cites this paper as Ranaweera et al. 2021
The Data Privacy and Privacy partitioning sections (pages unavailable) discuss privacy risks in MEC and a trusted local partition for deep-learning tasks. Neither says that training data is retained on edge devices to reduce leakage, or links that practice to a transmission bottleneck. Searches for local training data and the communication bottleneck found no passage establishing the claim. (LLM, conf=0.72)
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References 195 · Cited by 356
Research works printed but not linked: 12
- A. Reznik, Y. Fang, and S. Ullah, "MEC in an Enterprise Setting : A Solution Outline," ETSI White Paper #30, vol. 2, no. 30, 2018, last ac- cessed 16 May 2019. [Online]. Available: https://www.etsi.org/images/ files/ETSIWhitePapers/etsi wp30 MEC Enterprise FINAL.pdf
- U. Shahid and R. Krenz, "Mobile Cloud Development with Soft- ware Defined 5G Networks using NFV (Network Function Virtualiza- tion Technologies)," International Journal of Scientific & Engineering Research, vol. 6, no. 9, pp. 1552-1555, 2015.
- S. Kekki, W. Featherstone, Y. Fang, P. Kuure, A. Li, A. Ranjan, P. Debashish, F. Jianping, F. Danny, G. Verin, W. Kuo-Wei, K. Kim, A. Rohit, O. Andy, L. M. Contreras, and S. Scarpina, "MEC in 5G Networks," ETSI White Paper #28, vol. 28, no. 28, pp. 1-28, 2018, last accessed 16 May 2019. [Online]. Available: https://www.etsi.org/ images/files/ETSIWhitePapers/etsi wp28 mec in 5G FINAL.pdf
- ETSI, "Multi-access Edge Computing (MEC); Phase 2: Use Cases and Requirements," ETSI White Paper, vol. 2, 2018, last accessed 16 May 2019. [Online]. Available: https://www.etsi.org/deliver/etsi gs/MEC/001 099/002/02.01.01 60/gs MEC002v020101p.pdf
- M. Sabbagh, Y. Fei, T. Wahl, and A. A. Ding, "SCADET: A Side-Channel Attack Detection Tool for Tracking Prime+ Probe," in Proceedings of the International Conference on Computer-Aided Design, 2018, pp. 1-8.
- E. Gündüzhan and K. D. Brown, "Narrowband Satellite Commu- nications: Challenges and Emerging Solutions," John Hopkins APL technical Digest, 2015, vol. 33, 2015.
- Y. Siriwardhana, P. Porambage, M. Liyanage, J. S. Walia, M. Matinmikko-Blue, and M. Ylianttila, "Micro-Operator driven Local 5G Network Architecture for Industrial Internet," in IEEE Wireless Communications and Networking Conference (WCNC) 2019. IEEE, 2019, pp. 1-8.
- F. Giust, G. Verin, K. Antevski, J. Chou, Y. Fang, W. Featherstone, F. Fontes, D. Frydman, A. Li, A. Manzalini et al., "MEC deployments in 4G and evolution towards 5G," ETSI White Paper, vol. 24, pp. 1-24, 2018.
- D. Sun, J. Zhang, W. Fan, T. Wang, C. Liu, and W. Huang, "SPLM: Security Protection of Live Virtual Machine Migration in Cloud Com- puting," in Proceedings of the 4th ACM International Workshop on Security in Cloud Computing, 2016, pp. 2-9.
- A. Cavoukian et al., "Privacy by Design: The 7 Foundational Prin- ciples," Information and Privacy Commissioner of Ontario, Canada, vol. 5, 2009.
- P. Porambage, T. Kumar, M. Liyanage, J. Partala, L. Lovén, M. Ylianttila, and T. Seppänen. (2019) Sec-EdgeAI: AI for Edge Security Vs Security for Edge AI. Last accessed May 16, 2019. [On- line]. Available: https://www.researchgate.net/publication/330838792 Sec-EdgeAI AI for Edge Security Vs Security for Edge AI [193
- --. (2019) Sec-EdgeAI: A Vision for using Artificial Intelligence for Securing the Edge. Last accessed May 16, 2019. [Online]. Avail- able: https://www.researchgate.net/publication/330620630 EdgeAI A Vision for Privacy-preserving Machine Learning on the Edge
- Authors
- Ranaweera, P., Jurcut, A. D., & Liyanage, M.
- Affiliations
- University College Dublin (IE)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2021
- Volume
- 23
- Issue
- 2
- Pages
- 1078-1124
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W3135497297
- Cited by
- 356
- References
- 195
- Citations by year
- 2026: 28 · 2025: 70 · 2024: 88 · 2023: 81 · 2022: 69 · 2021: 20
- FWCI
- 28.88
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- Research Repository UCD (University College Dublin) (submittedVersion, cc-by)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by-nc-nd)
- Funders
- European Union under RESPONSE 5G (789658)
- Academy of Finland under 6Genesis Flagship Projects (318927)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Computer Networks and Communications › Cybersecurity and Information Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Security and Verification in Computing
- Keywords
- mobile edge computing, attack vectors, cellular networks, privacy preservation, security solutions
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