Vulnerability analysis of immunity-based intrusion detection systems using genetic and evolutionary hackers

Artificial immune systems ( AISs) are biologically inspired problem solvers that have been used successfully as intrusion detection systems ( IDSs). In this paper, we compare a genetic hacker with 12 evolutionary hackers based on particle swarm optimization (PSO) that have been effectively used as vulnerability analyzers ( red teams) for AIS-based IDSs. Our results show that the PSO-based red teams that use Clerc's constriction coefficient outperform those that do not. Our results also show that the three types of red teams ( genetic, basic PSO, and PSO with the constriction coefficient) have distinct search behaviors that are complimentary. (c) 2006 Elsevier B. V. All rights reserved.