NDLI: SPIT callers detection with unsupervised Random Forests classifier

Content Provider	IEEE Xplore Digital Library
Author	Toyoda, K. Sasase, I.
Copyright Year	2013
Description	Author affiliation: Dept. of Inf. & Comput. Sci., Keio Univ., Yokohama, Japan (Toyoda, K.; Sasase, I.)
Abstract	As VoIP (Voice over IP) grows rapidly, it is expected to prevail tremendous unsolicited advertisement calls, which type of calls is referred to SPIT (SPam over Internet Telephony). SPIT detection is more difficult to execute than email SPAM detection since the callee or SPIT detection system does not tell whether it is SPIT or legitimate call until he/she actually takes a call. Recently, many SPIT detection techniques are proposed by finding outliers of call patterns. However, most of these techniques suffer from setting a threshold to distinguish that the caller is legitimate or not and this could cause to high false negative rate or low true positive rate. This is because these techniques analyse call pattern by a single feature e.g. call frequency or average call duration. In this paper, we propose a multi-feature call pattern analysis with unsupervised Random Forests classifier, which is one of the excellent classification algorithms. We also propose two simple but helpful features for better classification. We show the effectiveness of Random Forests based classification without supervised training data and which features contribute to classification.
Starting Page	2068
Ending Page	2072
File Size	196100
Page Count	5
File Format	PDF
ISBN	9781467331227
ISSN	15503607
DOI	10.1109/ICC.2013.6654830
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-09
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Servers Accuracy Vegetation Feature extraction Decision trees Internet telephony Clustering methods
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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