Blind identification of source mobile devices using VoIP calls

Abstract

Sources such as speakers and environments from different communication devices produce signal variations that result in interference generated by different communication devices. Despite these convolutions, signal variations produced by different mobile devices leave intrinsic fingerprints on recorded calls, thus allowing the tracking of the models and brands of engaged mobile devices. This study aims to investigate the use of recorded Voice over Internet Protocol calls in the blind identification of source mobile devices. The proposed scheme employs a combination of entropy and mel-frequency cepstrum coefficients to extract the intrinsic features of mobile devices and analyzes these features with a multi-class support vector machine classifier. The experimental results lead to an accurate identification of 10 source mobile devices with an average accuracy of 99.72%.