Title: Bio-inspired algorithms for cybersecurity - a review of the state-of-the-art and challenges

Authors: Kwok Tai Chui; Ryan Wen Liu; Mingbo Zhao; Xinyu Zhang

Addresses: Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong ' Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan 430063, China ' School of Information Science and Technology, Donghua University, Shanghai 200051, China ' Navigation College, Dalian Maritime University, Dalian 116026, China

Abstract: It is witnessed that the popularity of the research in cybersecurity using bio-inspired algorithms (a key subset of natural algorithms) is ever-growing. As an emergent research area, researchers have devoted efforts to applying and comparing various bio-inspired algorithms to cybersecurity applications. It is necessary to have a systematic review of bio-inspired algorithms for cybersecurity to fill the gap in the missing research study on this topic. The research contributions of this review article are four-fold. It first highlights the foundation of the baseline and latest development of 12 popular bio-inspired algorithms in three categories namely ecology-based, evolutionary-based and swarm intelligence-based algorithms. A systematic review is conducted to synthesise and compare the research methodologies, results and limitations. In-depth discussion will be made on the shortlisted and highly cited articles. The tips to select appropriate algorithm or the combination of multiple algorithms have been reported, along with the pros and cons on the design and formulations. Future research directions will be presented to meet the trends and unexplored research.

Keywords: bio-inspired algorithms; cybersecurity; ecology-based algorithm; machine learning; evolutionary algorithms; multi-objective optimisation; swarm intelligence; trade-off solution.

DOI: 10.1504/IJBIC.2024.136199

International Journal of Bio-Inspired Computation, 2024 Vol.23 No.1, pp.1 - 15

Received: 31 Jan 2022
Accepted: 13 Jun 2022
Published online: 22 Jan 2024 *