Detection of anomalies in network traffic using L 2E for accurate speaker recognition

Umashanger Thayasivam, Sachin S. Shetty, Chinthaka Kuruwita, Ravi P. Ramachandran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Recently, widespread use of digital speech communication has spawned a multitude of Voice over IP (VoIP) applications. These applications require the ability to identify speakers in real time. One of the challenges in accurate speaker recognition is the inability to detect anomalies in network traffic generated by attacks on VoIP applications. This paper presents L 2E, an innovative approach to detect anomalies in network traffic for accurate speaker recognition. The L 2E method is capable of online speaker recognition from live packet streams of voice packets by performing fast classification over a defined subset of the features available in each voice packet. The experimental results show that L 2E is highly scalable and accurate in detecting a wide range of anomalies in network traffic.

Original languageEnglish (US)
Title of host publication2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012
Pages884-887
Number of pages4
DOIs
StatePublished - Oct 16 2012
Event2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012 - Boise, ID, United States
Duration: Aug 5 2012Aug 8 2012

Publication series

NameMidwest Symposium on Circuits and Systems
ISSN (Print)1548-3746

Other

Other2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012
CountryUnited States
CityBoise, ID
Period8/5/128/8/12

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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