Random forest algorithm with hill climbing algorithm to improve intrusion detection at endpoint and network
Satheesh Kumar Sekar, Palaniraj Rajidurai Parvathy, Latika Pinjarkar, Raman Latha, Mani Sathish, Munnangi Koti Reddy, Subbiah Murugan
Abstract
Cloud computing is a framework that enables end users to connect highly effective services and applications over the internet effortlessly. In the world of cloud computing, it is a critical problem to deliver services that are both safe and dependable. The best way to lessen the damage caused by entry into this environment is one of the primary security concerns. The fundamental advantage of a cooperative approach to intrusion detection system (IDS) is a superior vision of an action of network attack. This paper proposes a random forest (RF) algorithm with a hill-climbing algorithm (RFHC) to improve intrusion detection at the endpoint and network. Initially, it is used for feature selection, and the next process is to separate the intrusions detection. The feature selection is maintained by the hill climbing (HC) algorithm that chooses the best features. Then, we utilize the RF algorithm to separate the intrusion efficiently. The experimental results depict that the RFHC mechanism reached more acceptable results regarding recall, precision, and accuracy than a baseline mechanism. Moreover, it minimizes the miss detection ratio and enhances the intrusion detection ratio.
Keywords
Endpoint security; Feature selection; Hill climbing algorithm; Intrusion detection; Random forest algorithm
DOI:
http://doi.org/10.11591/ijeecs.v37.i1.pp134-142
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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).
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