Team for Research in
Ubiquitous Secure Technology

Citation
Yan Bai, Xiao Su, Bharat Bhargava. "Adaptive Voice Spam Control with User Behavior Analysis". Proc. 11th IEEE Int'l Conf. on High Performance Computing and Communications, 354-361, 2009.

Abstract
Spit (Spam over Internet Telephony), known as unsolicited bulk calls sent via VoIP networks¸ is a major problem that undermines the usability of VoIP. Countermeasures against spit face challenges in identifying and filtering spit in real time. A user-behavior based on three parameters (interaction, historical, and social ratio) is used to design an anti-spit technique. The rationale for the technique is that voice spammers behave significantly different from legitimate callers because of their revenue-driven motivations. The scheme uses adaptive training to determine filtering accuracy and estimates the legitimacy of the caller. The ideas can be implemented at the router level for detecting and achieving voice spam control. Compared to existing spit defending techniques, it is simple, fast and effective. Experiments are reported and measure the accuracy based on call intensity, call density, and the size of training data. The proposed scheme is applicable for detecting and filtering both machine-initiated and human-initiated spam calls, better protects VoIP calls against Sybil attacks and spammer behavior changes.

Electronic downloads

• HTML

  Yan Bai, Xiao Su, Bharat  Bhargava. <a
  href="http://www.truststc.org/pubs/689.html"
  >Adaptive Voice Spam Control with User Behavior
  Analysis</a>, Proc. 11th IEEE Int'l Conf. on High
  Performance Computing and Communications, 354-361, 2009.

• Plain text

  Yan Bai, Xiao Su, Bharat  Bhargava. "Adaptive Voice
  Spam Control with User Behavior Analysis". Proc. 11th
  IEEE Int'l Conf. on High Performance Computing and
  Communications, 354-361, 2009.

• BibTeX

  @inproceedings{BaiSuBhargava09_AdaptiveVoiceSpamControlWithUserBehaviorAnalysis,
      author = {Yan Bai and Xiao Su and Bharat  Bhargava},
      title = {Adaptive Voice Spam Control with User Behavior
                Analysis},
      booktitle = {Proc. 11th IEEE Int'l Conf. on High Performance
                Computing and Communications},
      pages = {354-361},
      year = {2009},
      abstract = {Spit (Spam over Internet Telephony), known as
                unsolicited bulk calls sent via VoIP networks¸ is
                a major problem that undermines the usability of
                VoIP. Countermeasures against spit face challenges
                in identifying and filtering spit in real time. A
                user-behavior based on three parameters
                (interaction, historical, and social ratio) is
                used to design an anti-spit technique. The
                rationale for the technique is that voice spammers
                behave significantly different from legitimate
                callers because of their revenue-driven
                motivations. The scheme uses adaptive training to
                determine filtering accuracy and estimates the
                legitimacy of the caller. The ideas can be
                implemented at the router level for detecting and
                achieving voice spam control. Compared to existing
                spit defending techniques, it is simple, fast and
                effective. Experiments are reported and measure
                the accuracy based on call intensity, call
                density, and the size of training data. The
                proposed scheme is applicable for detecting and
                filtering both machine-initiated and
                human-initiated spam calls, better protects VoIP
                calls against Sybil attacks and spammer behavior
                changes. },
      URL = {http://www.truststc.org/pubs/689.html}
  }
  

Posted by Xiao Su on 29 Mar 2010.
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