Impact of packet inter-arrival time features for online peer-to-peer (P2P) classification

• Main Authors: Abdalla, Bushra Mohammed Ali, Hamdan, Mosab, Mohammed, Mohammed Sultan, Bassi, Joseph Stephen, Ismail, Ismahani, Marsono, Muhammad Nadzir
• 格式: Article
• 语言: English
• 出版: Institute of Advanced Engineering and Science 2018
• 主题: TK Electrical engineering. Electronics Nuclear engineering
• 在线阅读: http://eprints.utm.my/id/eprint/81919/1/Bushra%20Mohammed%20Ali%202018_Impacof%20packeinter-arrival%20time.pdf; http://eprints.utm.my/id/eprint/81919/; http://dx.doi.org/10.11591/ijece.v8i4.pp2521-2530

Identification of bandwidth-heavy Internet traffic is important for network administrators to throttle high-bandwidth application traffic. Flow features based classification have been previously proposed as promising method to identify Internet traffic based on packet statistical features. The selection of statistical features plays an important role for accurate and timely classification. In this work, we investigate the impact of packet inter-arrival time feature for online P2P classification in terms of accuracy, Kappa statistic and time. Simulations were conducted using available traces from University of Brescia, University of Aalborg and University of Cambridge. Experimental results show that the inclusion of inter-arrival time (IAT) as an online feature increases simulation time and decreases classification accuracy and Kappa statistic.