Title: Modelling of advanced persistent threat attack monitoring based on the artificial fish swarm algorithm

Authors: Biaohan Zhang

Addresses: Fujian Key Lab of Agriculture IOT Application, School of Information Engineering, Sanming University, Sanming, Fujian, China

Abstract: In recent years, advanced persistent threat (APT) has become one of the important factors that threaten the network security. Aiming at the APT attack defence problem, this paper proposes an APT attack monitoring method based on the principle of artificial fish swarm algorithm. The attack monitoring model is established by imitating the behaviour of the artificial fish swarm. The model was used to dynamically monitor the environment, and the APT attack index was simulated with the food consistence to monitor the position of the highest APT attack index. The experimental results show that the monitoring model designed by this method can not only effectively monitor and forecast the attack target, but also has good expansibility and practicability.

Keywords: artificial fish swarm algorithm; advanced persistent threat attack; monitoring model.

DOI: 10.1504/IJCSE.2019.10026146

International Journal of Computational Science and Engineering, 2019 Vol.20 No.4, pp.550 - 557

Received: 13 Apr 2017
Accepted: 29 Oct 2017

Published online: 12 Jan 2020 *

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