skip to main content
10.1145/1854099.1854115acmotherconferencesArticle/Chapter ViewAbstractPublication PagessinConference Proceedingsconference-collections
research-article

A calculus for the qualitative risk assessment of policy override authorization

Published:07 September 2010Publication History

ABSTRACT

Policy override is gaining traction in the research community to improve the efficiency and usability of authorization mechanisms. These mechanisms turn the conventional privileges into a soft boundary that may be overridden by users in exceptional situations. The challenge for the practical deployment of the policy override mechanisms often is whether policy override is adequate and, if so, to which extent. In this paper, we propose a calculus to support this decision-making process. The calculus is based on proven risk assessment practices and derives a qualitative result on the adequacy for specific roles and override extents. Moreover, we developed a tool to support the policy override risk assessment. The calculus and the tool are briefly evaluated in two distinct contexts.

References

  1. C. Alberts, A. Dorofee, J. Stevens, and C. Woody. Introduction to the OCTAVE Approach. Carnegie-Mellon, Pittsburgh, PA, USA, August 2003.Google ScholarGoogle ScholarCross RefCross Ref
  2. Association of Certified Fraud Examiners (ACFE). Report to the nation on occupational fraud & abuse. 2006.Google ScholarGoogle Scholar
  3. Audit Commission. Opportunity Makes a Thief: an Analysis of Computer Abuse. Audit Commission Publication, London, UK, 1994.Google ScholarGoogle Scholar
  4. L. Badger. Providing a flexible security override for trusted systems. In CSFW, pages 115--121, 1990.Google ScholarGoogle ScholarCross RefCross Ref
  5. R. Baskerville. Information systems security design methods: implications for information systems development. ACM Comput. Surv., 25(4):375--414. 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. D. W. Britton and I. A. Brown. A security risk measurement for the RAdAC model. Master's thesis. Naval Postgraduate School Monterey, CA, March 2007.Google ScholarGoogle Scholar
  7. Bundesamt für Sicherheit in der Informationstechnik (BSI). BSI-Standard 100-2. IT-Grundschutz-Vorgehensweise. Version 2.0, 2008.Google ScholarGoogle Scholar
  8. P. L. Campbell and J. E. Stamp. A classification scheme for risk assessment methods. Technical Report SAND2004-4233, Sandia National Laboratories, 2004.Google ScholarGoogle Scholar
  9. D. Cappelli, A. Moore, R. F. Trzeciak, and T. J. Shimeall. Common sense guide to prevention and detection of insider threats 3rd edition - version 3.1 Technical report, CarnegieMellon, January 2009.Google ScholarGoogle Scholar
  10. P.-C. Cheng, P. Rohatgi, C. Keser, P. A. Karger, G. M. Wagner, and A. S. Reninger. Fuzzy multi-level security: An experiment on quantified risk-adaptive access control. In SP '07: Proceedings of the 2007 IEEE Symposium on Security and Privacy, pages 222--230, Washington, DC, USA, 2007. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. R. Choudhary. A policy based architecture for NSA RAdAC model. In Information Assurance Workshop (IAW 05), pages 294--301, June 2005.Google ScholarGoogle ScholarCross RefCross Ref
  12. I. Denley and S. W. Smith. Privacy in clinical information systems in secondary care. BMJ, 318(7194):1328--31, May 1999.Google ScholarGoogle ScholarCross RefCross Ref
  13. N. N. Diep, L. X. Hung, Y. Zhung, S. Lee, Y.-K. Lee and H. Lee. Enforcing access control using risk assessment. In Universal Multiservice Networks, 2007. ECUMN '07. Fourth European Conference on, pages 419--424, feb. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. N. Dimmock, A. Belokosztolszki, D. Eyers, J. Bacon, and K. Moody. Using trust and risk in role-based access control policies. In SACMAT '04: Proceedings of the ninth ACM symposium on Access control models and technologies, pages 156--162, New York, NY, US2004. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. T. Gilovich, D. W. Griffin, and D. Kahneman, editors, Heuristics and biases: the psychology of intuitive judgement. Cambridge University Press, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  16. F. A. Hayek. The use of knowledge in society. American Economic Review, 35:519--530, September 1945. Reprinted in F.A. Hayek (ed.), Individualism and Economic Order. London: Routledge and Kegan Paul.Google ScholarGoogle Scholar
  17. HIPAA. Break glass procedure: Granting emergency access to critical ePHI systems. Retrieved on Jan, 1, 2009, 2009.Google ScholarGoogle Scholar
  18. J. Jaisingh and J. Rees. Value at risk: A methodology for information security risk assessment. In In Proceedings of the INFORMS Conference on Information Systems and Technology, 2001.Google ScholarGoogle Scholar
  19. B. Karabacak and I. Sogukpinar. Isram: information security risk analysis method. Computers & Security 24(2):147--159, 2005.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. K. Lenstra and T. Voss. Information security risk assessment, aggregation, and mitigation. In H. Wang, J. Pieprzyk, and V. Varadharajan, editors, ACISP, volume 3108 of Lecture Notes in Computer Science, pages 391--401. Springer, 2004.Google ScholarGoogle Scholar
  21. J. J. Longsta, M. A. Lockyer, and M. G. Thick. A model of accountability, confidentiality and override for healthcare and other applications. In RBAC '00: Proceedings of the fifth ACM workshop on Role-based access control, pages 71--76, New York, NY, USA, 2000. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. G. Magklaras and S. Furnell. Insider threat prediction tool: Evaluating the probability of it misuse. Computers & Security, 21(1):62--73, 2002.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. J. A. Miller, M. Fan, S. Wu, I. B. Arpinar, A. P. Sheth, and K. J. Kochut. Security for the METEOR workflow management system. Technical report, UGA-CS-LDIS, University of Georgia, 1999.Google ScholarGoogle Scholar
  24. A. Moore, D. Cappelli, and R. F. Trzeciak. The "big picture" of insider IT sabotage across U.S. critical infrastructures. Technical Report CMU/SEI-2008-TR-009, CarnegieMellon, May 2008.Google ScholarGoogle ScholarCross RefCross Ref
  25. NIST. Fips 65: Guidelines for automatic data processing risk analysis. Technical report, NIST, 1975.Google ScholarGoogle Scholar
  26. NIST. Fips 191: Guideline for the analysis local area network security. Technical report, NIST, 1994.Google ScholarGoogle Scholar
  27. T. R. Peltier. Information security risk analysis. CRC press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. D. Povey. Optimistic security: a new access control paradigm. In NSPW '99: Proceedings of the 1999 workshop on New security paradigms, pages 40--45, New York, NY, USA, 2000. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. M. R. Randazzo, M. Keeney, E. Kowalski, D. Cappelli, and A. Moore. Insider threat study: Illicit cyber activity in the banking and finance sector. Technical Report CMU/SEI-2004-TR-021. CarnegieMellon, June 2005.Google ScholarGoogle Scholar
  30. E. Rissanen, B. S. Firozabadi, and M. J. Sergot. Towards a mechanism for discretionary overriding of access control. In B. Christianson, B. Crispo, J. A. Malcolm, and M. Roe, editors, Security Protocols Workshop, volume 3957 of Lecture Notes in Computer Science, pages 312--319. Springer, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. L. Røstad and O. Edsberg. A study of access control requirements for healthcare systems based on audit trails from access logs. In ACSAC, pages 175--186. IEEE Computer Society, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. J. H. Saltzer and M. D. Schroeder. The protection of information in computer systems. In Proceedings of the IEEE 63--9, 1975.Google ScholarGoogle ScholarCross RefCross Ref
  33. R. S. Sandhu, E. J. Coyne, H. L. Feinstein, and C. E. Youman. Role-based access control models. IEEE Computer, 29(2):38--47, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. E. E. Schultz. A framework for understanding and predicting insider attacks. Computers & Security, 21(6):526--531, 2002.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. W. Stallings and L. Brown. Computer security: principles and practice. Pearson Prentice Hall, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. G. Stevens and V. Wulf. A new dimension in access control: studying maintenance engineering across organizational boundaries. In CSCW '02: Proceedings of the 2002 ACM conference on Computer supported cooperative work, pages 196--205, New York, NY, USA, 2002. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. G. Stoneburner, A. Goguen, and A. Feringa. Risk management guide for information technology systems - NIST special publication 800-30. Technical report, National Institute of Standards and Technology, 2002.Google ScholarGoogle Scholar
  38. The CRAMM Manager. Cramm user guide issue 5.1. Technical report, Insight Consulting, 2005.Google ScholarGoogle Scholar
  39. R. Willison. Understanding the perpetration of employee computer crime in the organisational context. Information and Organization, 16(4):304--324, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. R. Willison and J. Backhouse. Opportunities for computer crime: considering systems risk froma criminological perspective. European Journal, 15(4), 2006.Google ScholarGoogle Scholar
  41. B. Wood. An insider threat model for adversary simulation. In R. H. Anderson, T. Bozek, T. Longsta, W. Meitzler, M. Skroch, and K. Van Wyk, editors, Research on Mitigating the Insider Threat to Information Systems #2. RAND, 2000.Google ScholarGoogle Scholar
  42. X. Zhao and M. E. Johnson. Access flexibility with escalation and audit. In WISE 2008: Twentieth Workshop on Information Systems and Economics, 2008.Google ScholarGoogle Scholar
  43. X. Zhao and M. E. Johnson. The value of escalation and incentives in managing information access. In Managing Information Risk and the Economics of Security. Springer-Verlag New York, Inc., 2009.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. A calculus for the qualitative risk assessment of policy override authorization

      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 Other conferences
        SIN '10: Proceedings of the 3rd international conference on Security of information and networks
        September 2010
        286 pages
        ISBN:9781450302340
        DOI:10.1145/1854099

        Copyright © 2010 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 September 2010

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate102of289submissions,35%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader