Empirical and Theoretical Evaluation of Active Probing Attacks and Their Countermeasures

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.

[1]  Claude E. Shannon,et al.  Communication theory of secrecy systems , 1949, Bell Syst. Tech. J..

[2]  Andrew Hintz,et al.  Fingerprinting Websites Using Traffic Analysis , 2002, Privacy Enhancing Technologies.

[3]  Lili Qiu,et al.  Statistical identification of encrypted Web browsing traffic , 2002, Proceedings 2002 IEEE Symposium on Security and Privacy.

[4]  Richard E. Newman,et al.  Performance analysis of a method for high level prevention of traffic analysis , 1992, [1992] Proceedings Eighth Annual Computer Security Application Conference.

[5]  Brenda Timmerman,et al.  A security model for dynamic adaptive traffic masking , 1998, NSPW '97.

[6]  Edward W. Felten,et al.  Timing attacks on Web privacy , 2000, CCS.

[7]  George Danezis,et al.  Mixminion: design of a type III anonymous remailer protocol , 2003, 2003 Symposium on Security and Privacy, 2003..

[8]  Richard E. Newman,et al.  High level prevention of traffic analysis , 1991, Proceedings Seventh Annual Computer Security Applications Conference.

[9]  R. Moddemeijer.  On estimation of entropy and mutual information of continuous distributions , 1989 .

[10]  C. D. Kemp,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[11]  Riccardo Bettati,et al.  On effectiveness of link padding for statistical traffic analysis attacks , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[12]  Paul Baran.  ON DISTRIBUTED COMMUNICATIONS: IX. SECURITY, SECRECY, AND TAMPER-FREE CONSIDERATIONS, , 1964 .

[13]  Anton Stiglic,et al.  Traffic Analysis Attacks and Trade-Offs in Anonymity Providing Systems , 2001, Information Hiding.

[14]  Paul F. Syverson,et al.  Anonymous connections and onion routing , 1997, Proceedings. 1997 IEEE Symposium on Security and Privacy (Cat. No.97CB36097).

[15]  David G. Stork,et al.  Pattern Classification , 1973 .

[16]  Dawn Xiaodong Song,et al.  Timing Analysis of Keystrokes and Timing Attacks on SSH , 2001, USENIX Security Symposium.

[17]  Robert Tappan Morris,et al.  Tarzan: a peer-to-peer anonymizing network layer , 2002, CCS '02.

[18]  Riccardo Bettati,et al.  IEEE TRANSACTIONS ON SYSTEMS , MAN , AND CYBERNETICS — PART A : SYSTEMS AND HUMANS , 2001 .

[19]  Jean-François Raymond,et al.  Traffic Analysis: Protocols, Attacks, Design Issues, and Open Problems , 2000, Workshop on Design Issues in Anonymity and Unobservability.

[20]  David Chaum,et al.  Untraceable electronic mail, return addresses, and digital pseudonyms , 1981, CACM.

[21]  Stephen T. Kent,et al.  Security Mechanisms in High-Level Network Protocols , 1983, CSUR.

[22]  Richard E. Newman,et al.  Performance analysis of a method for high level prevention of traffic analysis using measurements from a campus network , 1994, Tenth Annual Computer Security Applications Conference.

[23]  Brenda Timmerman,et al.  Secure dynamic adaptive traffic masking , 1999, NSPW '99.

[24]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[25]  Peter Sewell,et al.  Passive-attack analysis for connection-based anonymity systems , 2004, International Journal of Information Security.