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Attack Potential in Impact and Complexity

Published:29 August 2017Publication History

ABSTRACT

Vulnerability exploitation is reportedly one of the main attack vectors against computer systems. Yet, most vulnerabilities remain unexploited by attackers. It is therefore of central importance to identify vulnerabilities that carry a high 'potential for attack'. In this paper we rely on Symantec data on real attacks detected in the wild to identify a trade-off in the Impact and Complexity of a vulnerability in terms of attacks that it generates; exploiting this effect, we devise a readily computable estimator of the vulnerability's Attack Potential that reliably estimates the expected volume of attacks against the vulnerability. We evaluate our estimator performance against standard patching policies by measuring foiled attacks and demanded workload expressed as the number of vulnerabilities entailed to patch. We show that our estimator significantly improves over standard patching policies by ruling out low-risk vulnerabilities, while maintaining invariant levels of coverage against attacks in the wild. Our estimator can be used as a first aid for vulnerability prioritisation to focus assessment efforts on high-potential vulnerabilities.

References

  1. L. Allodi. The heavy tails of vulnerability exploitation. In Proc. of ESSoS'15, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  2. L. Allodi and F. Massacci. Comparing vulnerability severity and exploits using case-control studies. ACM Transaction on Information and System Security (TISSEC), 17(1), August 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. L. Allodi, F. Massacci, and J. Williams. The work-averse cyber attacker model. evidence from two million attack signatures. In Published in WEIS 2017. Available at https://ssrn.com/abstract=2862299, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  4. L. Allodi, S. Woohyun, and F. Massacci. Quantitative assessment of risk reduction with cybercrime black market monitoring. In In Proc. of IWCC'13, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. S. Chakradeo, B. Reaves, P. Traynor, and W. Enck. Mast: Triage for market-scale mobile malware analysis. In Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks, pages 13--24. ACM, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. S. Christey and B. Martin. Buying into the bias: why vulnerability statistics suck. https://www.blackhat.com/us-13/archives.html#Martin, July 2013.Google ScholarGoogle Scholar
  7. T. Dumitras and D. Shou. Toward a standard benchmark for computer security research: The worldwide intelligence network environment (wine). In Proc. of BADEGRS'11, pages 89--96. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. L. Evans. The effectiveness of safety belts in preventing fatalities. Accident Anal. & Prev., 18(3):229--241, 1986.Google ScholarGoogle ScholarCross RefCross Ref
  9. S. Frei, M. May, U. Fiedler, and B. Plattner. Large-scale vulnerability analysis. In Proc. of LSAD'06, pages 131--138. ACM, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. H. Holm and K. K. Afridi. An expert-based investigation of the common vulnerability scoring system. Computers & Security, 53:18--30, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. P. Mell, K. Scarfone, and S. Romanosky. A complete guide to the common vulnerability scoring system version 2.0. Technical report, FIRST, Available at http://www.first.org/cvss, 2007.Google ScholarGoogle Scholar
  12. K. Nayak, D. Marino, P. Efstathopoulos, and T. Dumitraş,. Some vulnerabilities are different than others. In Proc. of RAID'14, pages 426--446. Springer, 2014.Google ScholarGoogle Scholar
  13. PCI. Pci dss requirements and security assessment procedures, version 2.0. https://www.pcisecuritystandards.org/documents/pci_dss_v2.pdf, 2010.Google ScholarGoogle Scholar
  14. S. D. Quinn, K. A. Scarfone, M. Barrett, and C. S. Johnson. Sp 800-117. guide to adopting and using the security content automation protocol (scap) version 1.0. Technical report, NIST, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. K. Scarfone and P. Mell. An analysis of cvss version 2 vulnerability scoring. In Proc. of ESEM'09, pages 516--525, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Verizon. Verizon 2014 pci compliance report. Technical report, Verizon Enterprise, 2014.Google ScholarGoogle Scholar

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  1. Attack Potential in Impact and Complexity

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    • Published in

      cover image ACM Other conferences
      ARES '17: Proceedings of the 12th International Conference on Availability, Reliability and Security
      August 2017
      853 pages
      ISBN:9781450352574
      DOI:10.1145/3098954

      Copyright © 2017 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 29 August 2017

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      • short-paper
      • Research
      • Refereed limited

      Acceptance Rates

      ARES '17 Paper Acceptance Rate100of191submissions,52%Overall Acceptance Rate228of451submissions,51%

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