Distributed Cooperative Defense Against DDoS Attacks in Edge-Cloud Computing Networks: A Game-Theoretic Approach

As a promising computing paradigm, edge-cloud computing network integrates the ubiquitous computing resources on the cloud and edge servers to provide high-quality services, but is susceptible to complicated distributed denial-of-service (DDoS) attacks. Although some works have studied edge DDoS mitigation, the cooperative defense among cloud and edge servers considering the DDoS attacker’s strategic attack strategy is yet to be explored. In this paper, we model the interactions between the DDoS attacker and defenders as a two-stage dynamic game and propose a distributed cooperative defense scheme. In Stage I, the DDoS attacker strategically launches different amounts of malicious traffic to different edge servers to maximize the total filtering cost. In Stage II, edge servers under attack (i.e., defenders) filter their traffic on the cloud and other edge servers cooperatively to minimize the total filtering cost. The defenders’ problem in Stage II is NP-hard and we solve the problem by modeling defenders’ behaviors as a selfish filtering game. We prove that the selfish filtering game admits a unique Nash equilibrium (NE) with guaranteed social efficiency, and design both a centralized algorithm and a distributed algorithm to calculate the NE. For the attacker’s problem in Stage I, we first analyze a special case where each edge server has the same amount of normal traffic, and design a low-complexity algorithm to calculate the optimal attack strategy. We then analyze the general case where edge servers have different amounts of normal traffic, for which we derive the approximate optimal solution. Simulation results show that the DDoS attacker tends to launch attacks to all edge servers to reduce their cooperative defense capability, and our proposed distributed cooperative defense mechanism can effectively reduce the total filtering cost compared with existing benchmark defense mechanisms.