Advertisement

Language Modeling and Encryption on Packet Switched Networks

  • Kevin S. McCurley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4004)

Abstract

The holy grail of a mathematical model of secure encryption is to devise a model that is both faithful in its description of the real world, and yet admits a construction for an encryption system that fulfills a meaningful definition of security against a realistic adversary. While enormous progress has been made during the last 60 years toward this goal, existing models of security still overlook features that are closely related to the fundamental nature of communication. As a result there is substantial doubt in this author’s mind as to whether there is any reasonable definition of “secure encryption” on the Internet.

Keywords

Language Modeling Semantic Meaning Encryption System Message Space Bell System Technical Journal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Bellovin, S.M.: Probable plaintext cryptanalysis of the IP security protocols. In: Proc. of the Symp. on Network and Distributed System Security, pp. 155–160 (1997)Google Scholar
  2. 2.
    Bennett, C., Bessette, F., Brassard, G., Salvail, L., Smolin, J.: Experimental quantum cryptography. Journal of Cryptology 5, 3–28 (1992)CrossRefMATHGoogle Scholar
  3. 3.
    Biham, E., Shamir, A.: Differential fault analysis of secret key cryptosystems. In: Kaliski Jr., B.S. (ed.) CRYPTO 1997. LNCS, vol. 1294, pp. 513–525. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  4. 4.
    Boneh, D., Demillo, R.A., Lipton, R.J.: On the importance of checking cryptographic protocols for faults. In: Fumy, W. (ed.) EUROCRYPT 1997. LNCS, vol. 1233, pp. 37–51. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  5. 5.
    Chor, B., Kushilevitz, E.: Secret sharing over infinite domains. In: Brassard, G. (ed.) CRYPTO 1989. LNCS, vol. 435, pp. 299–306. Springer, Heidelberg (1990)Google Scholar
  6. 6.
    Danezis, G.: Traffic analysis of the HTTP protocol over TLS, http://homes.esat.kuleuven.be/~gdanezis/TLSanon.pdf
  7. 7.
    Danezis, G.: Introducing traffic analysis: Attacks, defences and public policy issues (2005), http://homes.esat.kuleuven.be/gdanezis/TAIntro.pdf
  8. 8.
    Diffie, W., Hellman, M.: New directions in cryptography. IEEE Transactions on Information Theory 22, 644–654 (1976)MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Goldreich, O.: A uniform-complexity treatment of encryption and zero-knowledge. Journal of Cryptology 6, 21–53 (1993)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Goldwasser, S., Micali, S.: Probabilistic encryption. Journal of Computer and System Sciences 28, 270–299 (1984)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Klein, A.: Detecting and preventing HTTP response splitting and HTTP request smuggling attacks at the TCP level, http://www.securityfocus.com/archive/1/408135
  12. 12.
    Kocher, P.: Cryptanalysis of Diffie-Hellman, RSA, DSS, and other cryptosystems using timing attacks. In: Coppersmith, D. (ed.) CRYPTO 1995. LNCS, pp. 171–183. Springer, Heidelberg (1995)Google Scholar
  13. 13.
    Kocher, P., Jaffe, J., Jun, B.: Differential power analysis. In: Wiener, M. (ed.) CRYPTO 1999. LNCS, vol. 1666, pp. 388–397. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  14. 14.
    Micali, S., Reyzin, L.: Physically observable cryptography. In: Naor, M. (ed.) TCC 2004. LNCS, vol. 2951, pp. 278–296. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    Moore, A.W., Zuev, D.: Internet traffic classification using Bayesian analysis techniques. In: SIGMETRICS 2005, pp. 50–60 (2005)Google Scholar
  16. 16.
    Newman, M.E.J.: The structure and function of complex networks. SIAM Review 45, 167–256 (2003)MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Shannon, C.E.: A mathematical theory of communication. Bell System Technical Journal 27, 379–423, 623–656 (1948)MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Shannon, C.E., Weaver, W.: The Mathematical Theory of Communication. University of Illinois Press, US (1949)MATHGoogle Scholar
  19. 19.
    Shannon, C.E.: Communication theory of secrecy systems. Bell Systems Technical Journal, 656–715 (1949)Google Scholar
  20. 20.
    Song, D.X., Wagner, D., Tian, X.: Timing analysis of keystrokes and timing attacks on ssh. In: Proc. USENIX Security Symposium, Washington, D.C, pp. 337–352 (2001)Google Scholar
  21. 21.
    Sun, Q., Simon, D.R., Wang, Y.-M., Russell, W., Padmanabhan, V.N., Qiu, L.: Statistical identificatoin of encrypted web browsing traffic. In: Proc. IEEE Security and Privacy Symp., pp. 19–30. Los Alamitos (2002)Google Scholar
  22. 22.
    Voydoc, V.L., Kent, S.: Security mechanisms in high-level network protocols. In: ACM Computing Surveys, pp. 135–171 (1983)Google Scholar
  23. 23.
    Thomas, J., Walsh, Kuhn, R.: Challenges in security voice over IP. IEEE Security and Privacy, 44–49, May/June (2005), http://csrc.nist.gov/staff/kuhn/walsh-kuhn-sp&05.pdf
  24. 24.
    Wright, C., Monrose, F., Masson, G.M.: HMM profiles for network traffic classification. In: ACM Conference on Computer and Communication Security, pp. 9–15 (2004)Google Scholar
  25. 25.
    Zhang, Y., Paxson, V.: Detecting stepping stones. In: Proc. 9th USENIX Security Symposium, pp. 171–184 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kevin S. McCurley
    • 1
  1. 1.GoogleUSA

Personalised recommendations