Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges
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Abstract (arXiv)
For various reasons, the cloud computing paradigm is unable to meet certain requirements (e.g. low latency and jitter, context awareness, mobility support) that are crucial for several applications (e.g. vehicular networks, augmented reality). To fulfil these requirements, various paradigms, such as fog computing, mobile edge computing, and mobile cloud computing, have emerged in recent years. While these edge paradigms share several features, most of the existing research is compartmentalised; no synergies have been explored. This is especially true in the field of security, where most analyses focus only on one edge paradigm, while ignoring the others. The main goal of this study is to holistically analyse the security threats, challenges, and mechanisms inherent in all edge paradigms, while highlighting potential synergies and venues of collaboration. In our results, we will show that all edge paradigms should consider the advances in other paradigms.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Feb 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 1; 2026: 2.
5 papers.
- 2021Machine Learning-based Orchestration of Containers: A Taxonomy and Future Directionscited by 7
- 2023Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learningcited by 2
- 2026Decentralized Multi-Agent Swarms for Autonomous Grid Security in Industrial IoT: A Consensus-based Approachcited by 2
- 2025A Hybrid Proactive And Predictive Framework For Edge Cloud Resource Managementcited by 0
- 2026Downsides of Smartness Across Edge-Cloud Continuum in Modern Industrycited by 0
- 2026Downsides of Smartness Across Edge-Cloud Continuum in Modern Industry31 Mar 2026
- 2026Decentralized Multi-Agent Swarms for Autonomous Grid Security in Industrial IoT: A Consensus-based Approach24 Jan 2026
- 2025A Hybrid Proactive And Predictive Framework For Edge Cloud Resource Management20 Nov 2025
- 2023Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning28 Mar 2023
- 2021Machine Learning-based Orchestration of Containers: A Taxonomy and Future Directions24 Jun 2021