Statistical Identification of Encrypted Web Browsing Traffic
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Timing analysis of keystrokes and timing attacks on SSH
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
Tor: the second-generation onion router
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Spot Me if You Can: Uncovering Spoken Phrases in Encrypted VoIP Conversations
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Proceedings of the 2009 ACM workshop on Cloud computing security
On privacy of skype VoIP calls
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
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Silence suppression, an essential feature of speech communications over the Internet, saves bandwidth by disabling voice packet transmission when silence is detected. On the other hand, silence suppression enables an adversary to recover talk patterns from packet timing. In this paper, we investigate privacy leakage through the silence suppression feature. More specifically, we propose a new class of traffic analysis attacks to encrypted speech communication with the goal of detecting speakers of encrypted speech communications. We evaluate the proposed attacks by extensive experiments over different type of networks including commercialized anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speakers of encrypted speech communications with high detection rates.