An Intrusion Detection Program (IDP) analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. In this talk, we present some of the challenges in designing efficient Intrusion Detection Systems (IDS) using nature inspired computation techniques, which could provide high accuracy, low false alarm rate and reduced number of features. Then we present some recent research results of developing distributed intrusion detection systems using genetic programming techniques. Further, we illustrate how intruder behavior could be captured using hidden Markov model and predict possible serious intrusions. Finally we illustrate the role of online risk assessment for intrusion prevention systems and some associated results. References: [1] Abraham A., Grosan C. and Martin-Vide C., Evolutionary Design of Intrusion Detection Programs, International Journal of Network Security, Vol.4, No.3, pp. 328-339, 2007. [2] Chen Y., Abraham A. and...
A. Abraham