On the Implications of Zipf’s Law in Passwords

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9878)

Abstract

Textual passwords are perhaps the most prevalent mechanism for access control over the Internet. Despite the fact that human-beings generally select passwords in a highly skewed way, it has long been assumed in the password research literature that users choose passwords randomly and uniformly. This is partly because it is easy to derive concrete (numerical) security results under the uniform assumption, and partly because we do not know what’s the exact distribution of passwords if we do not make a uniform assumption. Fortunately, researchers recently reveal that user-chosen passwords generally follow the Zipf’s law, a distribution which is vastly different from the uniform one.

In this work, we explore a number of foundational security implications of the Zipf-distribution assumption about passwords. Firstly, we how the attacker’s advantages against password-based cryptographic protocols (e.g., authentication, encryption, signature and secret share) can be 2–4 orders of magnitude more accurately captured (formulated) than existing formulation results. As password protocols are the most widely used cryptographic protocols, our new formulation is of practical significance. Secondly, we provide new insights into popularity-based password creation policies and point out that, under the current, widely recommended security parameters, usability will be largely impaired. Thirdly, we show that the well-known password strength metric \(\alpha \)-guesswork, which was believed to be parametric, is actually non-parametric in two of four cases under the Zipf assumption. Particularly, nine large-scale, real-world password datasets are employed to establish the practicality of our findings.

Keywords

User authentication Zipf’s law Password-based protocol Password creation policy Password strength metric 

References

  1. 1.
    Abdalla, M., Benhamouda, F., MacKenzie, P.: Security of the J-PAKE password-authenticated key exchange protocol. In: Proceedings of IEEE S&P 2015, pp. 571–587 (2015)Google Scholar
  2. 2.
    Abdalla, M., Benhamouda, F., Pointcheval, D.: Public-key encryption indistinguishable under plaintext-checkable attacks. In: Katz, J. (ed.) PKC 2015. LNCS, vol. 9020, pp. 332–352. Springer, Heidelberg (2015)Google Scholar
  3. 3.
    Bagherzandi, A., Jarecki, S., Saxena, N., Lu, Y.: Password-protected secret sharing. In: Proceedings of ACM CCS 2011, pp. 433–444 (2011)Google Scholar
  4. 4.
    Bellare, M.: Practice-oriented provable-security. In: Proceedings of ISC 1997, pp. 221–231 (1997)Google Scholar
  5. 5.
    Bellare, M., Hoang, V.T.: Adaptive witness encryption and asymmetric password-based cryptography. In: Katz, J. (ed.) PKC 2015. LNCS, vol. 9020, pp. 308–331. Springer, Heidelberg (2015)Google Scholar
  6. 6.
    Benhamouda, F., Blazy, O., Chevalier, C., Pointcheval, D., Vergnaud, D.: New techniques for SPHFs and efficient one-round PAKE protocols. In: Canetti, R., Garay, J.A. (eds.) CRYPTO 2013, Part I. LNCS, vol. 8042, pp. 449–475. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  7. 7.
    Blocki, J., Datta, A.: CASH: a cost asymmetric secure hash algorithm for optimal password protection. In: IEEE CSF 2016 (2016). arxiv.org/pdf/1509.00239v1.pdf
  8. 8.
    Bonneau, J.: The science of guessing: analyzing an anonymized corpus of 70 million passwords. In: Proceedings of IEEE S&P 2012, pp. 538–552 (2012)Google Scholar
  9. 9.
    Bonneau, J., Herley, C., Oorschot, P., Stajano, F.: The quest to replace passwords: a framework for comparative evaluation of web authentication schemes. In: Proceedings of IEEE S&P 2012, pp. 553–567 (2012)Google Scholar
  10. 10.
    Burr, W., Dodson, D., Perlner, R., Gupta, S., Nabbus, E.: NIST SP800-63-2: electronic authentication guideline. Technical report, National Institute of Standards and Technology, Reston, VA, August 2013Google Scholar
  11. 11.
    Byun, J.W.: Privacy preserving smartcard-based authentication system with provable security. Secur. Commun. Netw. 8(17), 3028–3044 (2015)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Carnavalet, X., Mannan, M.: A large-scale evaluation of high-impact password strength meters. ACM Trans. Inform. Syst. Secur. 18(1), 1–32 (2015)CrossRefGoogle Scholar
  13. 13.
    Castelluccia, C., Dürmuth, M., Perito, D.: Adaptive password-strength meters from markov models. In: Proceedings of NDSS 2012, pp. 1–15 (2012)Google Scholar
  14. 14.
    Chatterjee, R., Bonneau, J., Juels, A., Ristenpart, T.: Cracking-resistant password vaults using natural language encoders. In: Proceedings of IEEE S&P 2015, pp. 481–498 (2015)Google Scholar
  15. 15.
    Chen, L., Lim, H.W., Yang, G.: Cross-domain password-based authenticated key exchange revisited. ACM Trans. Inform. Syst. Secur. 16(4), 1–37 (2014)Google Scholar
  16. 16.
    Dürmuth, M., Freeman, D., Biggio, B.: Who are you? A statistical approach to measuring user authenticity. In: NDSS 2016, pp. 1–15 (2016)Google Scholar
  17. 17.
    Florêncio, D., Herley, C., van Oorschot, P.: An administrators guide to internet password research. In: Proceedings of USENIX LISA 2014, pp. 44–61 (2014)Google Scholar
  18. 18.
    Gjøsteen, K., Thuen, Ø.: Password-based signatures. In: Petkova-Nikova, S., Pashalidis, A., Pernul, G. (eds.) EuroPKI 2011. LNCS, vol. 7163, pp. 17–33. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  19. 19.
    Herley, C., Van Oorschot, P.: A research agenda acknowledging the persistence of passwords. IEEE Secur. Priv. 10(1), 28–36 (2012)CrossRefGoogle Scholar
  20. 20.
    Huang, X., Xiang, Y., Bertino, E., Zhou, J., Xu, L.: Robust multi-factor authentication for fragile communications. IEEE Trans. Depend. Secur. Comput. 11(6), 568–581 (2014)CrossRefGoogle Scholar
  21. 21.
    Huang, Z., Ayday, E., Hubaux, J., Juels, A.: Genoguard: protecting genomic data against brute-force attacks. In: Proceedings of IEEE S&P 2015, pp. 447–462 (2015)Google Scholar
  22. 22.
    Huh, J.H., Oh, S., Kim, H., et al.: Surpass: system-initiated user-replaceable passwords. In: Proceedings of CCS 2015, pp. 170–181 (2015)Google Scholar
  23. 23.
    Jarecki, S., Kiayias, A., Krawczyk, H., Xu, J.: Highly-efficient and composable password-protected secret sharing. In: Proceedings of IEEE EuroS&P 2016, pp. 276–291 (2016)Google Scholar
  24. 24.
    Jarecki, S., Krawczyk, H., Shirvanian, M., Saxena, N.: Device-enhanced password protocols with optimal online-offline protection. In: ASIACCS 2016, pp. 177–188 (2016)Google Scholar
  25. 25.
    Katz, J., Ostrovsky, R., Yung, M.: Efficient and secure authenticated key exchange using weak passwords. J. ACM 57(1), 1–41 (2009)MathSciNetCrossRefMATHGoogle Scholar
  26. 26.
    Katz, J., Vaikuntanathan, V.: Round-optimal password-based authenticated key exchange. J. Crypt. 26(4), 714–743 (2013)MathSciNetCrossRefMATHGoogle Scholar
  27. 27.
    Kiefer, F., Manulis, M.: Zero-knowledge password policy checks and verifier-based PAKE. In: Kutyłowski, M., Vaidya, J. (eds.) ESORICS 2014, Part II. LNCS, vol. 8713, pp. 295–312. Springer, Heidelberg (2014)Google Scholar
  28. 28.
    Li, Y., Wang, H., Sun, K.: A study of personal information in human-chosen passwords and its security implications. In: Proceedings of INFOCOM 2016, pp. 1–9 (2016)Google Scholar
  29. 29.
    Ma, J., Yang, W., Luo, M., Li, N.: A study of probabilistic password models. In: Proceedings of IEEE S&P 2014, pp. 689–704 (2014)Google Scholar
  30. 30.
    Malone, D., Maher, K.: Investigating the distribution of password choices. In: Proceedings of WWW 2012, pp. 301–310 (2012)Google Scholar
  31. 31.
    Martin, R.: Amid Widespread Data Breaches in China, December 2011. http://www.techinasia.com/alipay-hack/
  32. 32.
    Mick, J.: Russian Hackers Compile List of 10M+ Stolen Gmail. Yandex, Mailru, September 2014. http://t.cn/R4tmJE3
  33. 33.
    1st NSA Annual Best Scientific Cybersecurity Paper Competition, July 2013. http://cps-vo.org/group/sos/papercompetition2012
  34. 34.
    Schechter, S., Herley, C., Mitzenmacher, M.: Popularity is everything: a new approach to protecting passwords from statistical-guessing attacks. In: Proceedings of HotSec 2010, pp. 1–8 (2010)Google Scholar
  35. 35.
    Wang, D., He, D., Cheng, H., Wang, P.: fuzzyPSM: a new password strength meter using fuzzy probabilistic context-free grammars. In: Proceedings of DSN 2016, pp. 595–606 (2016)Google Scholar
  36. 36.
    Wang, D., Jian, G., Huang, X., Wang, P.: Zipf’s law in passwords. IEEE Trans. Inform. Foren. Secur. (2016, in press). http://t.cn/RqT51U8
  37. 37.
    Wang, D., Wang, P.: The emperor’s new password creation policies: an evaluationof leading web services and the effect of role in resisting against online guessing. In: Proceedings of ESORICS 2015, pp. 456–477 (2015)Google Scholar
  38. 38.
    Wang, Y.: Password protected smart card and memory stick authentication against off-line dictionary attacks. In: Gritzalis, D., Furnell, S., Theoharidou, M. (eds.) SEC 2012. IFIP AICT, vol. 376, pp. 489–500. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  39. 39.
    Yan, J., Blackwell, A.F., Anderson, R.J., Grant, A.: Password memorability and security: empirical results. IEEE Secur. Priv. 2(5), 25–31 (2004)CrossRefGoogle Scholar
  40. 40.
    Yi, X., Hao, F., Chen, L., Liu, J.K.: Practical threshold password-authenticated secret sharing protocol. In: Pernul, G., Ryan, P.Y.A., Weippl, E. (eds.) ESORICS. LNCS, vol. 9326, pp. 347–365. Springer, Heidelberg (2015). doi:10.1007/978-3-319-24174-6_18 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of EECSPeking UniversityBeijingChina
  2. 2.School of Software and MicroelectronicsPeking UniversityBeijingChina

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