Analysis of Skype and its Detection
Th. Rupachandra Singh1, Irengbam Tilokchan Singh2, Tejmani Sinam3
1Dr. Th. Rupachandra Singh, Department of Computer Science, Manipur University, Imphal, (Manipur), India.
2Irengbam Tilokchan Singh, Department of Computer Science, Manipur University, Imphal, (Manipur), India.
3Tejmani Sinam, Department of Computer Science, Manipur University, Imphal, (Manipur), India.
Manuscript received on 20 September 2016 | Revised Manuscript received on 30 September 2016 | Manuscript published on 30 September 2016 | PP: 1-6 | Volume-5 Issue-4, September 2016 | Retrieval Number: D1615095416©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper gives a complete analysis of Skype Traffic. Based on the analysis of Skype Traffic, we proposed a heuristic based detection method which classified the Skype Signaling and Skype Media Traffic. We properly categorized the Skype Media traffic as audio or video conversation. In this paper, we also propose a novel approach to identify VoIP Network Traffic in the first few seconds of initial state of communication. The proposed classifier works with Machine Learning Techniques based on the statistical features. The experimental results show that the proposed method can achieve over 99% accuracy for all testing dataset.
Keyword: Skype; Network Traffic Analysis; Traffic Classification; Machine Learning
Scope of the Article: Machine Learning