A Multiple-Swarm Particle Swarm Optimisation Scheme for Tracing Packets Back to the Attack Sources of Botnet - Hsiao-Chung Lin; Ping Wang; Wen-Hui Lin; Yu-Hsiang Huang (Applied Sciences, 2021)
Network intrusion detection systems that employ existing IP traceback (IPTBK) algorithms are generally unable to trace multiple attack sources. In these systems, the sampling mechanism only screens parts of the routing information, which leads to the tracing of the neighbour of the attack source and fails to identify the attack source. Theoretically, the multimodal optimisation problem cannot be solved for all of its multiple solutions using the traditional particle swarm optimisation (PSO) algorithm. The present study focuses on the use of multiple-swarm PSO (MSPSO) for recursively tracing attack paths back to a botnet’s multiple attack sources using the subgroup strategy. Specifically, the fitness of each path was calculated using a quasi-Newton gradient descent method to confirm the crucial path for successfully tracing the attack source. For multimodal optimisation problems, the MSPSO algorithm achieves an effective balance between individual particle exploitation and multiswarm exploration when premature convergence occurs. Thus, this algorithm accurately traces multiple attack sources. To verify the effectiveness of identifying Distributed Denial-Of-Service (DDoS) control centres, networks with various topology sizes (32–64 nodes) were simulated using ns-3 with the Boston University Representative Internet Topology Generator. The proposed A* search algorithm (minimal cost pathfinding algorithm) and MSPSO were used to identify the sources of simulated DDoS attacks. Compared with commonly available systems, the MSPSO algorithm performs better in multimodal optimisation problems, improves the accuracy of traceability analysis and reduces false responses for IPTBK problems.