A Survey of Intrusion Detection Systems using Evolutionary Computation

Intrusion detection is an indispensable part of a security system. Since new attacks are emerging every day, intrusion detection systems (IDS) play a key role in identifying possible attacks to the system and giving proper responses. IDSs should adapt to these new attacks and attack strategies, and continuously improve. How to develop effective, efficient and adaptive intrusion detection systems is a question that researchers have been working on for decades. Researchers have been exploring the suitability of different techniques to this research domain. The evolutionary computation inspired from natural evolution is one of the approaches increasingly studied. Some characteristics such as producing readable outputs for security experts, producing lightweight solutions, providing a set of solutions with different trade-offs between conflict objectives, make these techniques a promising candidate for the problem. In this study, we survey the proposed intrusion detection approaches based on evolutionary computation techniques found in the literature. Each major research area on intrusion detection is investigated thoroughly from the evolutionary computation point of view. Possible future research directions are also summarized for researchers.