Unsupervised SPITters detection scheme for unbalanced callers

Kentaro Toyoda; Mirang Park; Okazaki Naonobu

doi:10.1109/WAINA.2016.10

Unsupervised SPITters detection scheme for unbalanced callers

Kentaro Toyoda, Mirang Park, Okazaki Naonobu

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

1 Citation (Scopus)

Abstract

As the IP-based telephony service is getting popular, new attackers called SPITters (Spam over Internet Telephony callers) who advertise products and conduct a survey is being emerged and it is urgent demand to detect them. Recently, a novel unsupervised SPITters detection scheme, which leverages a clustering algorithm, has been proposed. However, this scheme does not work well when the SPITters account for a small fraction of the entire caller. In this paper, we propose a new unsupervised SPITters detection scheme by adding artificial data to solve such unbalanced situation. Our scheme will avoid some of the legitimate callers from being clustered into the SPITters' cluster and the classification performance will be improved. We show the efficiency of the proposed scheme by means of computer simulation with real and artificial call log datasets.

Original language	English
Title of host publication	Proceedings - IEEE 30th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	64-68
Number of pages	5
ISBN (Electronic)	9781509018574
DOIs	https://doi.org/10.1109/WAINA.2016.10
Publication status	Published - 2016 May 17
Externally published	Yes
Event	30th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016 - Crans-Montana, Switzerland Duration: 2016 Mar 23 → 2016 Mar 25

Other

Other	30th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016
Country/Territory	Switzerland
City	Crans-Montana
Period	16/3/23 → 16/3/25

Keywords

Security
SPIT
Unsupervised machine learning
VoIP

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems
Information Systems and Management
Modelling and Simulation

Access to Document

10.1109/WAINA.2016.10

Cite this

Unsupervised SPITters detection scheme for unbalanced callers. / Toyoda, Kentaro; Park, Mirang; Naonobu, Okazaki.
Proceedings - IEEE 30th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 64-68 7471174.

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

Toyoda, K, Park, M & Naonobu, O 2016, Unsupervised SPITters detection scheme for unbalanced callers. in Proceedings - IEEE 30th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016., 7471174, Institute of Electrical and Electronics Engineers Inc., pp. 64-68, 30th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016, Crans-Montana, Switzerland, 16/3/23. https://doi.org/10.1109/WAINA.2016.10

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abstract = "As the IP-based telephony service is getting popular, new attackers called SPITters (Spam over Internet Telephony callers) who advertise products and conduct a survey is being emerged and it is urgent demand to detect them. Recently, a novel unsupervised SPITters detection scheme, which leverages a clustering algorithm, has been proposed. However, this scheme does not work well when the SPITters account for a small fraction of the entire caller. In this paper, we propose a new unsupervised SPITters detection scheme by adding artificial data to solve such unbalanced situation. Our scheme will avoid some of the legitimate callers from being clustered into the SPITters' cluster and the classification performance will be improved. We show the efficiency of the proposed scheme by means of computer simulation with real and artificial call log datasets.",

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ER -

Unsupervised SPITters detection scheme for unbalanced callers

Abstract

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Keywords

ASJC Scopus subject areas

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