skip to main content
10.1145/1978942.1979321acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

Of passwords and people: measuring the effect of password-composition policies

Authors Info & Claims
Published:07 May 2011Publication History

ABSTRACT

Text-based passwords are the most common mechanism for authenticating humans to computer systems. To prevent users from picking passwords that are too easy for an adversary to guess, system administrators adopt password-composition policies (e.g., requiring passwords to contain symbols and numbers). Unfortunately, little is known about the relationship between password-composition policies and the strength of the resulting passwords, or about the behavior of users (e.g., writing down passwords) in response to different policies. We present a large-scale study that investigates password strength, user behavior, and user sentiment across four password-composition policies. We characterize the predictability of passwords by calculating their entropy, and find that a number of commonly held beliefs about password composition and strength are inaccurate. We correlate our results with user behavior and sentiment to produce several recommendations for password-composition policies that result in strong passwords without unduly burdening users.

References

  1. A. Adams, M. A. Sasse, and P. Lunt. Making passwords secure and usable. In HCI 97, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. Bishop and D. V. Klein. Improving system security via proactive password checking. Computers & Security, 14(3):233--249, 1995.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Bonneau and S. Preibusch. The password thicket: technical and market failures in human authentication on the web. In Proc. (online) of WEIS'10, June 2010.Google ScholarGoogle Scholar
  4. W. E. Burr, D. F. Dodson, and W. T. Polk. Electronic authentication guideline. Technical report, NIST, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Florêncio and C. Herley. A large-scale study of web password habits. In Proc. WWW'07, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. D. Florêncio and C. Herley. Where do security policies come from? In Proc. SOUPS '10, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. P. Inglesant and M. A. Sasse. The true cost of unusable password policies: password use in the wild. In Proc. ACM CHI'10, pages 383--392, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. B. Ives, K. R. Walsh, and H. Schneider. The domino effect of password reuse. C. ACM, 47(4):75--78, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J. L. Massey. Guessing and entropy. In Proc. IEEE ISIT'94, page 204, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  10. G. Miller. Note on the bias of information estimates. Info. Th. Psych.: Problems and Methods, 1955.Google ScholarGoogle Scholar
  11. L. Paninski. Estimation of entropy and mutual information. Neural Comp., 15(6):1191--1253, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. R. W. Proctor, M.-C. Lien, K.-P. L. Vu, E. E. Schultz, and G. Salvendy. Improving computer security for authentication of users: Influence of proactive password restrictions. Behavior Res. Methods, Instruments, & Computers, 34(2):163--169, 2002.Google ScholarGoogle Scholar
  13. S. Schechter, C. Herley, and M. Mitzenmacher. Popularity is everything: A new approach to protecting passwords from statistical-guessing attacks. In Proc. HotSec'10, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. C. E. Shannon. A mathematical theory of communication. ACM SIGMOBILE Mobile Comp. Comm. Rev., 5(1), 1949. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. C. E. Shannon. Prediction and entropy of printed english. Bell Systems Tech. J., 30:50--64, 1951.Google ScholarGoogle ScholarCross RefCross Ref
  16. R. Shay and E. Bertino. A comprehensive simulation tool for the analysis of password policies. Int. J. Info. Sec., 8(4):275--289, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. R. Shay, S. Komanduri, P. Kelley, P. Leon, M. Mazurek, L. Bauer, N. Christin, and L. Cranor. Encountering stronger password requirements: user attitudes and behaviors. In Proc. SOUPS'10, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. J. M. Stanton, K. R. Stam, P. Mastrangelo, and J. Jolton. Analysis of end user security behaviors. Comp. & Security, 24(2):124--133, 2005.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. A. Vance. If your password is 123456, just make it hackme. New York Times, http://www.nytimes.com/2010/01/21/technology/21password.html, January 2010, retrieved September 2010.Google ScholarGoogle Scholar
  20. K.-P. L. Vu, R. W. Proctor, A. Bhargav-Spantzel, B.-L. B. Tai, and J. Cook. Improving password security and memorability to protect personal and organizational information. Int. J. of Human-Comp. Studies, 65(8):744--757, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. M. Weir, S. Aggarwal, M. Collins, and H. Stern. Testing metrics for password creation policies by attacking large sets of revealed passwords. In Proceedings of the 17th ACM conference on Computer and communications security, CCS '10, pages 162--175, New York, NY, USA, 2010. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Y. Zhang, F. Monrose, and M. K. Reiter. The security of modern password expiration: An algorithmic framework and empirical analysis. In Proc. ACM CCS'10, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. M. Zviran and W. J. Haga. Password security: an empirical study. J. Mgt. Info. Sys., 15(4):161--185, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Of passwords and people: measuring the effect of password-composition policies
          Index terms have been assigned to the content through auto-classification.

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Conferences
            CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
            May 2011
            3530 pages
            ISBN:9781450302289
            DOI:10.1145/1978942

            Copyright © 2011 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 7 May 2011

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article

            Acceptance Rates

            CHI '11 Paper Acceptance Rate410of1,532submissions,27%Overall Acceptance Rate6,199of26,314submissions,24%

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader