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Voice-Pishing Detection Algorithm Based on Minimum Classification Error Technique  

Lee, Kye-Hwan (Department of Electronics Engineering, Inha University)
Chang, Joon-Hyuk (Department of Electronics Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.46, no.3, 2009 , pp. 138-142 More about this Journal
Abstract
We propose an effective voice-phishing detection algorithm based on discriminative weight training. The detection of voice phishing is performed based on a Gaussian mixture model (GMM) incorporaiting minimum classification error (MCE) technique. Actually, the MCE technique is based on log-likelihood from the decoding parameter of the SMV(Selectable Mode Vocoder) directly extracted from the decoding process in the mobile phone. According to the experimental result, the proposed approach is found to be effective for the voice phishing detection.
Keywords
Selectable Mode Vocoder (SMV); Gaussian Mixture Model (GMM); Minimum Classification Error (MCE);
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Times Cited By KSCI : 1  (Citation Analysis)
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