Modelling of advanced persistent threat attack monitoring based on the artificial fish swarm algorithm
by Biaohan Zhang
International Journal of Computational Science and Engineering (IJCSE), Vol. 20, No. 4, 2019

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.

Online publication date: Sun, 12-Jan-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com