IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Real Time Cryptanalysis of A5/1 on a PC
FSE '00 Proceedings of the 7th International Workshop on Fast Software Encryption
Billing attacks on SIP-based VoIP systems
WOOT '07 Proceedings of the first USENIX workshop on Offensive Technologies
Denial of service attack and prevention on SIP VoIP infrastructures using DNS flooding
Proceedings of the 1st international conference on Principles, systems and applications of IP telecommunications
Instant Ciphertext-Only Cryptanalysis of GSM Encrypted Communication
Journal of Cryptology
Language identification of encrypted VoIP traffic: Alejandra y Roberto or Alice and Bob?
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
Spot Me if You Can: Uncovering Spoken Phrases in Encrypted VoIP Conversations
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Acoustic Analysis of Adult Speaker Age
Speaker Classification I
Speech Under Stress: Analysis, Modeling and Recognition
Speaker Classification I
A Study of Acoustic Correlates of Speaker Age
Speaker Classification II
IEEE Transactions on Information Theory
Speaker recognition from encrypted VoIP communications
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Privacy streamliner: a two-stage approach to improving algorithm efficiency
Proceedings of the second ACM conference on Data and Application Security and Privacy
k-indistinguishable traffic padding in web applications
PETS'12 Proceedings of the 12th international conference on Privacy Enhancing Technologies
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Transmitting voice communication over untrusted networks puts personal information at risk. Although voice streams are typically encrypted to prevent unwanted eavesdropping, additional features of voice communication protocols might still allow eavesdroppers to discover information on the transmitted content and the speaker. We develop a novel approach for unveiling the identity of speakers who participate in encrypted voice communication, solely by eavesdropping on the encrypted traffic. Our approach exploits the concept of voice activity detection (VAD), a widely used technique for reducing the bandwidth consumption of voice traffic. We show that the reduction of traffic caused by VAD techniques creates patterns in the encrypted traffic, which in turn reveal the patterns of pauses in the underlying voice stream. We show that these patterns are speaker-characteristic, and that they are sufficient to undermine the anonymity of the speaker in encrypted voice communication. In an empirical setup with 20 speakers our analysis is able to correctly identify an unknown speaker in about 48% of all cases. Our work extends and generalizes existing work that exploits variable bit-rate encoding for identifying the conversation language and content of encrypted voice streams.