抄録
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.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | Proceedings - IEEE 30th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016 |
| 出版者 | Institute of Electrical and Electronics Engineers Inc. |
| ページ | 64-68 |
| ページ数 | 5 |
| ISBN（電子版） | 9781509018574 |
| DOI | |
| 出版物ステータス | Published - 2016 5 17 |
| 外部発表 | Yes |
| イベント | 30th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016 - Crans-Montana, Switzerland 継続期間: 2016 3 23 → 2016 3 25 |
Other
| Other | 30th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016 |
|---|---|
| 国 | Switzerland |
| 市 | Crans-Montana |
| 期間 | 16/3/23 → 16/3/25 |
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ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
- Information Systems and Management
- Modelling and Simulation
これを引用
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.研究成果: Conference contribution
}
TY - GEN
T1 - Unsupervised SPITters detection scheme for unbalanced callers
AU - Toyoda, Kentaro
AU - Park, Mirang
AU - Naonobu, Okazaki
PY - 2016/5/17
Y1 - 2016/5/17
N2 - 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.
AB - 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.
KW - Security
KW - SPIT
KW - Unsupervised machine learning
KW - VoIP
UR - http://www.scopus.com/inward/record.url?scp=84983499619&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983499619&partnerID=8YFLogxK
U2 - 10.1109/WAINA.2016.10
DO - 10.1109/WAINA.2016.10
M3 - Conference contribution
AN - SCOPUS:84983499619
SP - 64
EP - 68
BT - Proceedings - IEEE 30th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -