文档介绍：Modeling Intrusion Detection Systems Using Linear
ic Programming Approach
Srinivas Mukkamala, Andrew H. Sung, Ajith Abrham*
Department puter Science, New Mexico Tech, Socorro, NM 87801
*Department puter Science, Oklahoma State University, Tulsa, OK 74106
{srinivas,sung}***@, @
Abstract-This paper investigates the suitability of linear ic programming
(LGP) technique to model efficient intrusion detection systems, while
comparing its performance with artificial works and support vector
machines. Due to increasing incidents of cyber attacks and, building effective
intrusion detection systems (IDSs) are essential for protecting information
systems security, and yet it remains an elusive goal and a great challenge. We
also investigate key feature indentification for building efficient and effective
IDSs. Through a variety parative experiments, it is found that, with
appropriately chosen population size, program size, crossover rate and mutation
rate, linear ic programs could outperform support vector machines and
works in terms of detection accuracy. Using key features gives
notable performance in terms of detection accuracies. However the difference in
accuracy tends to be small in a few cases.
1 Introduction
Since most of the intrusions can be located by examining patterns of user activities
and