A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Untraceable electronic mail, return addresses, and digital pseudonyms
Communications of the ACM
ISDN-MIXes: Untraceable Communication with Small Bandwidth Overhead
Kommunikation in Verteilten Systemen, Grundlagen, Anwendungen, Betrieb, GI/ITG-Fachtagung
Statistical Identification of Encrypted Web Browsing Traffic
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Low-Cost Traffic Analysis of Tor
SP '05 Proceedings of the 2005 IEEE Symposium on Security and Privacy
Tor: the second-generation onion router
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Enhanced Skype traffic identification
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Devices that tell on you: privacy trends in consumer ubiquitous computing
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
On flow correlation attacks and countermeasures in mix networks
PET'04 Proceedings of the 4th international conference on Privacy Enhancing Technologies
On privacy leakage through silence suppression
ISC'10 Proceedings of the 13th international conference on Information security
| Hi-index | 0.00 |
Skype is one of the most popular voice-over-IP (VoIP) service providers. One of the main reasons for the popularity of Skype VoIP services is its unique set of features to protect privacy of VoIP calls such as strong encryption, proprietary protocol, unknown codec, dynamic path selection, and constant packet rate. In this paper, we propose a class of passive traffic analysis attacks to compromise privacy of Skype VoIP calls. The proposed attacks are based on application-level features extracted from VoIP call traces. The proposed attacks are evaluated by extensive experiments over different types of networks including commercialized anonymity networks and our campus network. The experiments show that the proposed traffic analysis attacks can detect speaker and speech of Skype calls with 0.33 and 0.44 detection rate, about 30-fold and 15-fold improvement over random guess respectively.