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

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

doi:10.1109/MWSCAS.2012.6292162

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 proceeding › Conference 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 language	English (US)
Title of host publication	2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012
Pages	884-887
Number of pages	4
DOIs	https://doi.org/10.1109/MWSCAS.2012.6292162
State	Published - 2012
Event	2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012 - Boise, ID, United States Duration: Aug 5 2012 → Aug 8 2012

Publication series

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

Other

Other	2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012
Country/Territory	United States
City	Boise, ID
Period	8/5/12 → 8/8/12

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/MWSCAS.2012.6292162

Cite this

@inproceedings{3a5a8930d7a94f199fa4924ceb7117f6,

title = "Detection of anomalies in network traffic using L 2E for accurate speaker recognition",

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.",

author = "Umashanger Thayasivam and Shetty, {Sachin S.} and Chinthaka Kuruwita and Ramachandran, {Ravi P.}",

year = "2012",

doi = "10.1109/MWSCAS.2012.6292162",

language = "English (US)",

isbn = "9781467325264",

series = "Midwest Symposium on Circuits and Systems",

pages = "884--887",

booktitle = "2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012",

note = "2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012 ; Conference date: 05-08-2012 Through 08-08-2012",

}

Thayasivam, U, Shetty, SS, Kuruwita, C & Ramachandran, RP 2012, Detection of anomalies in network traffic using L ₂E for accurate speaker recognition. in 2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012., 6292162, Midwest Symposium on Circuits and Systems, pp. 884-887, 2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012, Boise, ID, United States, 8/5/12. https://doi.org/10.1109/MWSCAS.2012.6292162

Detection of anomalies in network traffic using L ₂E for accurate speaker recognition. / Thayasivam, Umashanger; Shetty, Sachin S.; Kuruwita, Chinthaka et al.
2012 IEEE 55th International Midwest Symposium on Circuits and Systems, MWSCAS 2012. 2012. p. 884-887 6292162 (Midwest Symposium on Circuits and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Detection of anomalies in network traffic using L 2E for accurate speaker recognition

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AB - 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.

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