Bio-Inspired Modified Bees Colony Feature Selection based Intrusion Detection System for Cloud Computing Application.

Abstract

Social networks have become an important part of everyday life. As soon as 5G services are launched in the near future, the annual IP network flow is expected to increase significantly. In the event of security threats, network attacks become more diverse and difficult to detect. The IDS of the network protection system has the task of detecting malicious activity on the Internet. This study proposes a modified method for selecting the function of bee colonies to solve IDS problems. For our experiential study, we use a KDD99 dataset that comprises five modules: Normal, Query, DOS, U2R, and R2L. And also discusses the feature selection process because it can develop the enactment of classification. To select a function, a modified bee colony (MBC) feature selection method was chosen in this article. MBC is a novel feature selection method. There is an exact comparison between the proposed method and various existing methods. Our effects show that the proposed scheme gives 99.46% betterclassification accuracy results than the various existing methods.