Revealing Influenced Selected Feature for P2p Botnet Detection.

Wan Ahmad Ramzi WY; FaizalM A; Rudy Fadhlee M D; Nur Hidayah M S

Author(s)

Wan Ahmad Ramzi WY Masjid Tanah Community College, Ministry Of Higher Education Malaysia, Paya Rumput, 78300 Masjid Tanah, Melaka,

FaizalM A Information Security, Digital Forensic, and Computer Networking (INSFORNET), Department of Computer System and Communication, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

Rudy Fadhlee M D Information Security, Digital Forensic, and Computer Networking (INSFORNET), Department of Computer System and Communication, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

Nur Hidayah M S Information Security, Digital Forensic, and Computer Networking (INSFORNET), Department of Computer System and Communication, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

Abstract

P2P botnet has become a serious security threat for computer networking systems. Botnet attack causes a great financial loss and badly impact the information and communication technology (ICT) system. Current botnet detection mechanisms have limitations and flaws to deal with P2P botnets which famously known for their complexity and scalable attack. Studies show that botnets behavior can be detected based on several detection features. However, some of the feature parameters may not represent botnet behavior and may lead to higher false alarm detection rate. In this paper, we reveal selected feature that influences P2P botnets detection. The result obtained by selecting features shows detection attack rate of 99.74%.

Publication Details

Page(s) 500-506

DOI DOI not available

Published Journal: International Journal of Communication Networks and Information Security, Volume: 9, Issue: 3, Year: 2017

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