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Survey of Uses of Evolutionary Computation Algorithms and Swarm Intelligence for Network Intrusion Detection

Saber Elsayed

School of Engineering and Information Technology University of New South Wales at Canberra, Canberra, Australia

E-mail Address: s.elsayed@adfa.edu.au

Corresponding author.

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Ruhul Sarker

School of Engineering and Information Technology University of New South Wales at Canberra, Canberra, Australia

E-mail Address: r.sarker@adfa.edu.au

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, and

Daryl Essam

School of Engineering and Information Technology University of New South Wales at Canberra, Canberra, Australia

E-mail Address: d.essam@adfa.edu.au

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https://doi.org/10.1142/S146902681550025XCited by:10 (Source: Crossref)

Abstract

Many infrastructures, such as those of finance and banking, transportation, military and telecommunications, are highly dependent on the Internet. However, as the Internet’s underlying structural protocols and governance can be disturbed by intruders, for its smooth operation, it is important to minimize such disturbances. Of the available techniques for achieving this, computational intelligence methodologies, such as evolutionary algorithms and swarm intelligence approaches, are popular and have been successfully applied to detect intrusions. In this paper, we present an overview of these techniques and related literature on intrusion detection, analyze their research contributions, compare their approaches and discuss new research directions which will provide useful insights for intrusion detection researchers and practitioners.

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