Joint Resource Allocation and Intrusion Prevention System Deployment for Edge Computing

Abstract

Distributed Denial-of-Service (DDoS) attack is critical to latency-critical systems such as Multi-Access Edge Computing (MEC) as it significantly increases the response delay of the victim service. An intrusion prevention system (IPS) is a promising solution to defend against such attacks. Still, there will be a trade-off between IPS deployment and application resource reservation as IPS deployment will reduce the computational resources for MEC applications. In this work, we propose a game-theoretic framework to study the joint computational resource allocation and IPS deployment in the MEC architecture. Given the expected attack strength and end-user demands, we study the pricing strategy of the MEC platform operator (MPO) and purchase strategy of the application service providers (ASPs). The best responses of both MPO and ASPs are derived theoretically. Based on the best responses, we propose an efficient algorithm to derive the Stackelberg equilibrium. The properties and optimality in the efficiency of the equilibrium are analyzed through simulations. The results confirm that the proposed solutions significantly increase the social welfare of the system.