Abstract

Establishing secure voice, video and text over Internet (VoIP) communications is a crucial task necessary to prevent eavesdropping and man-in-the-middle attacks. The traditional means of secure session establishment (e.g., those relying upon PKI or KDC) require a dedicated infrastructure and may impose unwanted trust onto third-parties. (popular instances such as PGPfone and Zfone), in contrast, provide a purely peer-to-peer user-centric secure mechanism claiming to completely address the problem of wiretapping. The secure association mechanism in Crypto Phones is based on cryptographic protocols employing Short Authenticated Strings (SAS) validated by end users over the voice medium. The security of Crypto Phones crucially relies on the assumption that the voice channel, over which SAS is validated by the users, provides the properties of integrity and source authentication. In this paper, we challenge this assumption, and report on automated SAS voice imitation man-in-the-middle attacks} that can compromise the security of Crypto Phones in both two-party and multi-party settings, even if users pay due diligence. The first attack, called the short voice reordering attack, builds arbitrary SAS strings in a victim's voice by reordering previously eavesdropped SAS strings spoken by the victim. The second attack, called the short voice morphing attack, builds arbitrary SAS strings in a victim's voice from a few previously eavesdropped sentences (less than 3 minutes) spoken by the victim. We design and implement our attacks using off-the-shelf speech recognition/synthesis tools, and comprehensively evaluate them with respect to both manual detection (via a user study with 30 participants) and automated detection. The results demonstrate the effectiveness of our attacks against three prominent forms of SAS encodings: numbers, PGP word Lists and Madlib sentences. These attacks can be used by a wiretapper to compromise the confidentiality and privacy of Crypto Phones voice, video and text communications (plus authenticity in case of text conversations).

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