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Evolutionary Computation Algorithms for Detecting Known and Unknown Attacks

  • Hasanen AlyasiriEmail author
  • John A. Clark
  • Daniel Kudenko
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11359)

Abstract

Threats against the internet and computer networks are becoming more sophisticated, with attackers using new attacks or modifying existing ones. Security teams have major difficulties in dealing with large numbers of continuously evolving threats. Various artificial intelligence algorithms have been deployed to analyse such threats. In this paper, we explore the use of Evolutionary Computation (EC) techniques to construct behavioural rules for characterising activities observed in a system. The EC framework evolves human readable solutions that provide an explanation of the logic behind its evolved decisions, offering a significant advantage over existing paradigms. We examine the potential application of these algorithms to detect known and unknown attacks. The experiments were conducted on modern datasets.

Keywords

Intrusion Detection System Unknown attacks Evolutionary computation 

Notes

Acknowledgements

Hasanan Alyasiri would like to thank the Iraqi Ministry of Higher Education and Scientific Research and the University of Kufa for supporting his PhD study. John Clark is supported by the EPSRC DAASE Programme Grant EP/J017515/1.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Hasanen Alyasiri
    • 1
    Email author
  • John A. Clark
    • 2
  • Daniel Kudenko
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK
  2. 2.Department of Computer ScienceUniversity of SheffieldSheffieldUK

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