An Intelligent Multimedia Traffic Classifier with Security Applications

نویسندگان

  • Oge Marques
  • Alvaro Fonseca
  • Liam M. Mayron
چکیده

The volume of multimedia traffic transmitted over the Internet has increased significantly over the past few years. As a result, the need to analyze and classify multimedia traffic has become more acute. Conventional packetor header-based analysis has limitations; a deeper understanding of the actual multimedia content may be necessary. This paper presents a machine learning-based multimedia traffic classification solution that performs content analysis on video sequences with potential applications in security. Experimental results show that the proposed solution can classify video sequences as suspicious based on inspection of their visual content.

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تاریخ انتشار 2007