Evolutionary Design of Intrusion Detection Programs

Ajith Abraham ； Crina Grosan ； Carlos Martin-Vide

《International Journal of Network Security》 4卷3期 (2007/05) Pp. 328-339

https://doi.org/10.6633/IJNS.200705.4(3).12

並列摘要

Intrusion detection is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of intrusions, defined as attempts to compromise the confidentiality, integrity, availability, or to bypass the security mechanisms of a computer or network. This paper proposes the development of an Intrusion Detection Program (IDP) which could detect known attack patterns. An IDP does not eliminate the use of any preventive mechanism but it works as the last defensive mechanism in securing the system. Three variants of genetic programming techniques namely Linear Genetic Programming (LGP), Multi-Expression Programming (MEP) and Gene Expression Programming (GEP) were evaluated to design IDP. Several indices are used for comparisons and a detailed analysis of MEP technique is provided. Empirical results reveal that genetic programming technique could play a major role in developing IDP, which are light weight and accurate when compared to some of the conventional intrusion detection systems based on machine learning paradigms.

並列關鍵字

Intrusion detection program ； genetic programming ； machine learning ； light weight intrusion detection system