FEDMGame: Distributed Fairness-Aware DDoS Mitigation in Mobile Edge Computing

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Authors: Jie Pan, Guangming Cui, Jintao Wu, Yiwen Zhang, Jianhua Zhang, Xiaolong Xu
Cited by: 3

Abstract

The proliferation of mobile edge computing (MEC) enhances its capability to deliver low-latency services, while the geographical distribution and limited resources of edge servers simultaneously make them increasingly susceptible to distributed denial-of-service (DDoS) attacks. Existing edge DDoS mitigation strategies primarily focus on improving serviceability, that is, the number of mitigated requests, or reducing latency, yet often overlook systematic modeling of load fairness among edge servers. This omission can lead to resource imbalance, local overload, and ultimately degrade the system's long-term service performance and responsiveness to attacks. To address this issue, we propose the Fairness-aware Edge DDoS Mitigation (FairEDM) problem, which explicitly incorporates load fairness into the mitigation objective. Specifically, we first formulate FairEDM as a constrained optimization problem and prove its NP-hardness. To obtain a sub-optimal solution, we further model it as a game named FEDMGame, and design a distributed strategy formulation (FEDM-DSF) algorithm, based on multi-player best response dynamics. The resulting Nash equilibrium serves as a feasible mitigation strategy. Both theoretical analysis and experimental results validate the effectiveness and efficiency of the proposed FEDMGame framework.

Fields of Study & Subjects

IoT and Edge/Fog Computing Network Security and Intrusion Detection Software-Defined Networks and 5G

Publication details

Journal / source
IEEE Transactions on Dependable and Secure Computing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
23
Issue
3
Pages
4986–4999
Publication date
5 January 2026
Language
EN