Principles of a computer immune system
NSPW '97 Proceedings of the 1997 workshop on New security paradigms
Swarm intelligence
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Network Intrusion Detection: An Analyst's Handbook
Network Intrusion Detection: An Analyst's Handbook
Intrusion Signatures and Analysis
Intrusion Signatures and Analysis
Computer Intrusion Detection and Network Monitoring: A Statistical Viewpoint
Computer Intrusion Detection and Network Monitoring: A Statistical Viewpoint
A Statistical Method for Profiling Network Traffic
Proceedings of the Workshop on Intrusion Detection and Network Monitoring
An immunological model of distributed detection and its application to computer security
An immunological model of distributed detection and its application to computer security
Architecture for an Artificial Immune System
Evolutionary Computation
Revisiting LISYS: parameters and normal behavior
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
| Hi-index | 0.00 |
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.