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Survey on evolutionary computation methods for cybersecurity of mobile ad hoc networks

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Abstract

In this paper, a comprehensive survey of evolutionary computation (EC) methods for cybersecurity of mobile ad hoc networks (MANETs) is presented. Typically, EC methods are named based on the natural processes inspiring them, such as swarm intelligence (e.g., ant colony optimization, artificial bee colony, and particle swarm optimization), evolutionary algorithms (e.g., genetic algorithms, genetic programming, grammatical evolution, and differential evolution), artificial immune systems, and evolutionary games analyzing strategic interactions among different population types. We introduce these methods with their typical applications, and commonly used algorithms to improve cybersecurity within the scope of MANETs. Ongoing and speedy topology changes, multi-hop communication, non-hierarchical organization, and power and computational limitations are among the intrinsic characteristics of MANETs causing cybersecurity vulnerabilities. We describe basic defense mechanisms in MANETs for vulnerability detection, attack deterrence, prevention and recovery, and risk mitigation. We classify principal applications of EC as intrusion detection, trust management, and cryptography in cybersecurity systems to counter measure adversarial activities.

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Acknowledgements

This research is supported by D01_W911SR-14-2-0001-0014. The contents of this document represent the views of the authors and are not necessarily the official views of, or endorsed by, the US Government, Department of Defense, Department of the Army or US Army Communications-Electronic RD&E Center. Dr. Cem Safak Sahin is currently an MIT Lincoln Laboratory employee; no Laboratory funding or resources were used to produce the result/findings reported in this publication.

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  1. NYC College of Technology, City University of New York, Brooklyn, NY, 11201, USA

    Janusz Kusyk

  2. City College of New York, City University of New York, New York, NY, 10031, USA

    M. Umit Uyar

  3. MIT Lincoln Laboratory, Lexington, MA, 02420, USA

    Cem Safak Sahin

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Kusyk, J., Uyar, M.U. & Sahin, C.S. Survey on evolutionary computation methods for cybersecurity of mobile ad hoc networks. Evol. Intel. 10, 95–117 (2018). https://doi.org/10.1007/s12065-018-0154-4

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