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Quantifying the security effectiveness of firewalls and DMZs

Published:10 April 2018Publication History

ABSTRACT

Firewalls and Demilitarized Zones (DMZs) are two mechanisms that have been widely employed to secure enterprise networks. Despite this, their security effectiveness has not been systematically quantified. In this paper, we make a first step towards filling this void by presenting a representational framework for investigating their security effectiveness in protecting enterprise networks. Through simulation experiments, we draw useful insights into the security effectiveness of firewalls and DMZs. To the best of our knowledge, these insights were not reported in the literature until now.

References

  1. Ehab Al-Shaer, Hazem Hamed, Raouf Boutaba, and Masum Hasan. 2005. Conflict classification and analysis of distributed firewall policies. IEEE journal on selected areas in communications 23, 10 (2005), 2069--2084. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. D. Chakrabarti, Y. Wang, C. Wang, J. Leskovec, and C. Faloutsos. 2008. Epidemic thresholds in real networks. ACM Trans. Inf. Syst. Secur. 10, 4 (2008), 1--26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Geoff Chappell. {n. d.}. kernel-mode windows. https://www.geoffchappell.com/studies/windows/km/index.htm?tx=10. ({n. d.}).Google ScholarGoogle Scholar
  4. Gaofeng Da, Maochao Xu, and Shouhuai Xu. 2014. A New Approach to Modeling and Analyzing Security of Networked Systems. In Proceedings of the 2014 Symposium on the Science of Security (HotSoS'14). 6:1--6:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Rinku Dewri, Nayot Poolsappasit, Indrajit Ray, and Darrell Whitley. 2007. Optimal security hardening using multi-objective optimization on attack tree models of networks. In Proceedings of the 14th ACM conference on Computer and communications security. ACM, 204--213. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Anup K Ghosh, Aaron Schwartzbard, and Michael Schatz. 1999. Learning Program Behavior Profiles for Intrusion Detection.. In Workshop on Intrusion Detection and Network Monitoring, Vol. 51462. 1--13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Yujuan Han, Wnelian Lu, and Shouhuai Xu. 2014. Characterizing the Power of Moving Target Defense via Cyber Epidemic Dynamics. In Proc. 2014 Symposium on the Science of Security (HotSoS'14). 10:1--10:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Ray Hunt. 1998. Internet/Intranet firewall security-policy, architecture and transaction services. Computer Communications 21, 13 (1998), 1107--1123. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Eric M Hutchins, Michael J Cloppert, and Rohan M Amin. 2011. Intelligence-driven computer network defense informed by analysis of adversary campaigns and intrusion kill chains. Leading Issues in Information Warfare & Security Research 1, 1 (2011), 80.Google ScholarGoogle Scholar
  10. Somesh Jha, Oleg Sheyner, and Jeannette Wing. 2002. Two formal analyses of attack graphs. In Computer Security Foundations Workshop, 2002. Proceedings. 15th IEEE. IEEE, 49--63. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. X. Li, P. Parker, and S. Xu. 2011. A Stochastic Model for Quantitative Security Analysis of Networked Systems. IEEE Transactions on Dependable and Secure Computing 8, 1 (2011), 28--43. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Mateusz. {n. d.}. Windows WIN32K.SYS System Call Table. http://j00ru.vexillium.org/syscalls/win32k/32/. ({n. d.}).Google ScholarGoogle Scholar
  13. Alain Mayer, Avishai Wool, and Elisha Ziskind. 2000. Fang: A firewall analysis engine. In Security and Privacy, 2000. S&P 2000. Proceedings. 2000 IEEE Symposium on. IEEE, 177--187. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Dan McWhorter. 2013. APT1: exposing one of China's cyber espionage units. Mandiant. com 18 (2013).Google ScholarGoogle Scholar
  15. David M. Nicol, William H. Sanders, and Kishor S. Trivedi. 2004. Model-Based Evaluation: From Dependability to Security. IEEE Trans. Dependable Sec. Comput. 1, 1 (2004), 48--65. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Steven Noel and Sushil Jajodia. 2017. A Suite of Metrics for Network Attack Graph Analytics. Springer International Publishing, Cham, 141--176.Google ScholarGoogle Scholar
  17. The Forum of Incident Response and Security Teams FIRST. 2015. The Common Vulnerability Scoring System (CVSS). (June 2015). https://www.first.org/cvssGoogle ScholarGoogle Scholar
  18. Marcus Pendleton, Richard Garcia-Lebron, Jin-Hee Cho, and Shouhuai Xu. 2017. A survey on systems security metrics. ACM Computing Surveys (CSUR) 49, 4 (2017), 62. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Nayot Poolsappasit, Rinku Dewri, and Indrajit Ray. 2012. Dynamic security risk management using bayesian attack graphs. IEEE Transactions on Dependable and Secure Computing 9, 1 (2012), 61--74. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. Ramos, M. Lazar, R. H. Filho, and J. J. P. C. Rodrigues. 2017. Model-Based Quantitative Network Security Metrics: A Survey. IEEE Communications Surveys Tutorials 19, 4 (2017), 2704--2734.Google ScholarGoogle ScholarCross RefCross Ref
  21. Oleg Sheyner, Joshua Haines, Somesh Jha, Richard Lippmann, and Jeannette M Wing. 2002. Automated generation and analysis of attack graphs. In Security and privacy, 2002. Proceedings. 2002 IEEE Symposium on. IEEE, 273--284. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Deb Shinder. {n. d.}. SolutionBase: Strengthen network defenses by using a DMZ. https://www.techrepublic.com/article/solutionbase-strengthen-network-defenses-by-using-a-dmz/. ({n. d.}).Google ScholarGoogle Scholar
  23. Mahbod Tavallaee, Ebrahim Bagheri, Wei Lu, and Ali A Ghorbani. 2009. A detailed analysis of the KDD CUP 99 data set. In Computational Intelligence for Security and Defense Applications, 2009. CISDA 2009. IEEE Symposium on. IEEE, 1--6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Y. Wang, D. Chakrabarti, C. Wang, and C. Faloutsos. 2003. Epidemic Spreading in Real Networks: An Eigenvalue Viewpoint. In Proc. of the 22nd IEEE Symposium on Reliable Distributed Systems (SRDS'03). 25--34.Google ScholarGoogle Scholar
  25. Avishai Wool. 2004. A quantitative study of firewall configuration errors. Computer 37, 6 (2004), 62--67. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Maochao Xu, Gaofeng Da, and Shouhuai Xu. 2015. Cyber Epidemic Models with Dependences. Internet Mathematics 11, 1 (2015), 62--92.Google ScholarGoogle ScholarCross RefCross Ref
  27. Maochao Xu and Shouhuai Xu. 2012. An Extended Stochastic Model for Quantitative Security Analysis of Networked Systems. Internet Mathematics 8, 3 (2012), 288--320.Google ScholarGoogle ScholarCross RefCross Ref
  28. Shouhuai Xu. 2014. Cybersecurity Dynamics. In Proc. Symposium on the Science of Security (HotSoS'14). 14:1--14:2. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Shouhuai Xu, Wenlian Lu, and Li Xu. 2012. Push- and Pull-based Epidemic Spreading in Arbitrary Networks: Thresholds and Deeper Insights. ACM Transactions on Autonomous and Adaptive Systems (ACM TAAS) 7, 3 (2012), 32:1--32:26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Shouhuai Xu, Wenlian Lu, Li Xu, and Zhenxin Zhan. 2014. Adaptive Epidemic Dynamics in Networks: Thresholds and Control. ACM Transactions on Autonomous and Adaptive Systems (ACM TAAS) 8, 4 (2014), 19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Ren Zheng, Wenlian Lu, and Shouhuai Xu. 2015. Active Cyber Defense Dynamics Exhibiting Rich Phenomena. In Proc. 2015 Symposium on the Science of Security (HotSoS'15). 2:1--2:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. R. Zheng, W. Lu, and S. Xu. 2017. Preventive and Reactive Cyber Defense Dynamics Is Globally Stable. IEEE Transactions on Network Science and Engineering PP, 99 (2017), 1--1.Google ScholarGoogle Scholar

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        • Published in

          cover image ACM Other conferences
          HoTSoS '18: Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security
          April 2018
          163 pages
          ISBN:9781450364553
          DOI:10.1145/3190619
          • General Chairs:
          • Munindar Singh,
          • Laurie Williams,
          • Program Chairs:
          • Rick Kuhn,
          • Tao Xie

          Copyright © 2018 ACM

          © 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the United States Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 10 April 2018

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