Spam detection in voice-over-IP calls through semi-supervised clustering

Proceedings of the International Conference on Dependable Systems and Networks

Volumn , Issue , 2009, Pages 307-316

  Wu, Yu Sung ^d   Bagchi, Saurabh ^a   Singh, Navjot ^b   Wita, Ratsameetip ^c  

^a PURDUE UNIVERSITY   (United States)

^b AVAYA LABS RESEARCH   (United States)

^c CHULALONGKORN UNIVERSITY   (Thailand)

^d NONE

Author keywords

Clustering; Semi supervised learning; Spam detection; Spit detection; Voice over IP systems

Indexed keywords

CALL TRACES; COMPUTATION TIME; DETECTION ACCURACY; ERROR PRONES; IP TELEPHONY; RUNTIMES; SEMI-SUPERVISED CLUSTERING; SEMI-SUPERVISED LEARNING; SIGNALING TRAFFIC; SOFT REAL TIME; SPAM DETECTION; USER FEEDBACK; VOICE OVER IP; VOICE TRAFFIC; VOIP SYSTEMS;

INTERNET; INTERNET PROTOCOLS; INTERNET TELEPHONY; LEARNING ALGORITHMS; SPAMMING; SUPERVISED LEARNING; TELEPHONE SYSTEMS;

VOICE/DATA COMMUNICATION SYSTEMS;

EID: 70450078363     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DSN.2009.5270323     Document Type: Conference Paper

References (20)

1. VOIPSA, "VoIP Threat Taxonomy," 2008.
2. Y. S. Wu, S. Bagchi, S. Garg, and N. Singh, "SCIDIVE: a stateful and cross protocol intrusion detection architecture for voice-over-IP environments," in DSN, 2004, pp. 433-442.
3. H. Sengar, D. Wijesekera, H. Wang, and S. Jajodia, "VoIP Intrusion Detection Through Interacting Protocol State Machines," in DSN, 2006, pp. 393-402.
4. C. J. J. Rosenberg, "RFC 5039 : The Session Initiation Protocol (SIP) and Spam," 2008.
5. D. Shin, J. Ahn, and C. Shim, "Progressive Multi Gray-Leveling: A Voice Spam Protection Algorithm," IEEE Network, vol. 20, pp. 18-24, 2006.
6. M. Bilenko, S. Basu, and R. J. Mooney, "Integrating constraints and metric learning in semi-supervised clustering," in ICML, 2004, pp. 81-88.
7. J. Quittek, S. Niccolini, S. Tartarelli, M. Stiemerling, M. Brunner, and T. Ewald, "Detecting SPIT Calls by Checking Human Communication Patterns," in ICC, 2007, pp. 1979-1984.
8. R. MacIntosh and D. Vinokurov, "Detection and mitigation of spam in IP telephony networks using signaling protocol analysis," in IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication, 2005, pp. 49-52.
9. P. Kolan and R. Dantu, "Socio-technical defense against voice spamming," ACM Transactions on Autonomous and Adaptive Systems (TAAS), vol. 2, 2007.
10. J. MacQueen, "Some methods for classification and analysis of multivariate observations," in the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1967, p. 14.
11. P. Haider, U. Brefeld, and T. Scheffer, "Supervised clustering of streaming data for email batch detection," in ICML, 2007, pp. 345-352.
12. M. Sasaki and H. Shinnou, "Spam Detection Using Text Clustering," in International Conference on Cyberworlds, 2005.
13. C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Mining and Knowledge Discovery, vol. 2, pp. 121-167, 1998.
14. G. Druck, C. Pal, A. McCallum, and X. Zhu, "Semisupervised classification with hybrid generative/discriminative methods," in KDD, 2007, pp. 280-289.
15. K. Bennett and A. Demiriz, "Semi-supervised support vector machines," Advances in Neural Information processing systems, pp. 368-374, 1999.
16. J. Rosenberg, "RFC 3261 - SIP: Session Initiation Protocol," 2002.
17. H. Schulzrinne, "RFC 1889 - RTP: A Transport Protocol for Real-Time Applications," 1996.
18. N. Grira, M. Crucianu, and N. Boujemaa, "Unsupervised and Semi-supervised Clustering: a Brief Survey," A Review of Machine Learning Techniques for Processing Multimedia Content', Report of the MUSCLE European Network of Excellence (FP6), 2004.
19. T. Finley and T. Joachims, "Supervised clustering with support vector machines," in ICML, 2005, pp. 217-224.
20. voip-info.org, "Asterisk SIP Media Path."