A security model for dynamic adaptive traffic masking
NSPW '97 Proceedings of the 1997 workshop on New security paradigms
Proceedings of the 7th ACM conference on Computer and communications security
Security Mechanisms in High-Level Network Protocols
ACM Computing Surveys (CSUR)
Untraceable electronic mail, return addresses, and digital pseudonyms
Communications of the ACM
Traffic analysis: protocols, attacks, design issues, and open problems
International workshop on Designing privacy enhancing technologies: design issues in anonymity and unobservability
Tarzan: a peer-to-peer anonymizing network layer
Proceedings of the 9th ACM conference on Computer and communications security
Traffic Analysis Attacks and Trade-Offs in Anonymity Providing Systems
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Statistical Identification of Encrypted Web Browsing Traffic
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Mixminion: Design of a Type III Anonymous Remailer Protocol
SP '03 Proceedings of the 2003 IEEE Symposium on Security and Privacy
On Effectiveness of Link Padding for Statistical Traffic Analysis Attacks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Anonymous Connections and Onion Routing
SP '97 Proceedings of the 1997 IEEE Symposium on Security and Privacy
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Timing analysis of keystrokes and timing attacks on SSH
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
NetCamo: camouflaging network traffic for QoS-guaranteed mission critical applications
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
SAS: a scalar anonymous communication system
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
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A variety of remote sensing attacks allow adversaries to break flow confidentiality and gather mission-critical information in distributed systems. Such attacks are easily supplemented by active probing attacks, where additional workload (e.g., ping packets) is injected into the victim system. This paper presents statistical pattern recognition as a fundamental technology to evaluate the effectiveness of active probing attacks. Our theoretical analysis and empirical results show that even if sophisticated approaches of link padding are used, sample entropy of probing packets’ round trip time is an effective and robust feature statistic to discover the user payload traffic rate, which is important for maintaining anonymous communication. Extensive experiments on local network, campus network, and the Internet were carried out to validate the system security predicted by the theoretical analysis. We give some guidelines to reduce the effectiveness of such active probing attacks.