Detecting Anomalous Process Behaviour using Second Generation Artificial Immune Systems
Jamie Twycross, Uwe Aickelin, Amanda Whitbrook
International Journal of Unconventional Computing | Old City Publishing | Published : 2010
Artificial Immune Systems have been successfully applied to a number of problem domains including fault tolerance and data mining, but have been shown to scale poorly when applied to computer intrusion detection despite the fact that the biological immune system is a very effective anomaly detector. This may be because AIS algorithms have previously been based on the adaptive immune system and biologically-naive models. This paper focuses on describing and testing a more complex and biologically-authentic AIS model, inspired by the interactions between the innate and adaptive immune systems. Its performance on a realistic process anomaly detection problem is shown to be better than standard ..View full abstract
Awarded by EPSRC
This research is supported by the EPSRC (GR/S47809/01) and HP Labs.