Voice-Pishing Detection Algorithm Based on Minimum Classification Error Technique
Kye-Hwan Lee, Joon‐Hyuk Chang · Journal of the Institute of Electronics Engineers of Korea · 2009
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.