Network intrusion detection method based on improved ant colony algorithm combined with cluster analysis in cloud computing environment Online publication date: Thu, 03-Nov-2022
by Xifeng Wang; Xiaoluan Zhang
International Journal of Information Technology and Management (IJITM), Vol. 21, No. 4, 2022
Abstract: Aiming at the low detection accuracy of traditional clustering algorithm in intrusion detection under cloud computing platform, a network intrusion detection method based on improved ant colony algorithm combined with clustering analysis is proposed. The purpose of the ant colony clustering module is to distinguish most of the clusters belonging to the same type again by clustering algorithm. Each feature vector is used as the clustering centre to process and analyse them, so as to realise the separation of legal and illegal acts of network data as far as possible. Experiments on KDDcup99 data set show that the accuracy of the algorithm can achieve at 94.3% for DoS intrusion types and 94.1% for U2R intrusion types, which is higher than that of the contrast methods. It further proves that the proposed improved algorithm has a good clustering effect.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Information Technology and Management (IJITM):
Login with your Inderscience username and 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
Our Blog 
Follow us on Twitter 
Visit us on Facebook