Measuring network security using dynamic bayesian network

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Measuring network security using dynamic bayesian network

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Conference on Computer and Communications Security archive
Proceedings of the 4th ACM workshop on Quality of protection table of contents

Alexandria, Virginia, USA

SESSION: Security measurement table of contents

Pages 23-30

Year of Publication: 2008

ISBN:978-1-60558-321-1

Authors

Marcel Frigault	Concordia University, Montreal, PQ, Canada
Lingyu Wang	Concordia University, Montreal, PQ, Canada
Anoop Singhal	National Institute of Standards and Technology, Gaithersburg, MD, USA
Sushil Jajodia	George Mason University, Fairfax, VA, USA

Sponsors

SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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ABSTRACT

Given the increasing dependence of our societies on networked information systems, the overall security of these systems should be measured and improved. Existing security metrics have generally focused on measuring individual vulnerabilities without considering their combined effects. Our previous work tackle this issue by exploring the causal relationships between vulnerabilities encoded in an attack graph. However, the evolving nature of vulnerabilities and networks has largely been ignored. In this paper, we propose a Dynamic Bayesian Networks (DBNs)-based model to incorporate temporal factors, such as the availability of exploit codes or patches. Starting from the model, we study two concrete cases to demonstrate the potential applications. This novel model provides a theoretical foundation and a practical framework for continuously measuring network security in a dynamic environment.

REFERENCES

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	1	Paul Ammann , Duminda Wijesekera , Saket Kaushik, Scalable, graph-based network vulnerability analysis, Proceedings of the 9th ACM conference on Computer and communications security, November 18-22, 2002, Washington, DC, USA [doi>10.1145/586110.586140]
	2	Xiangdong An , Dawn Jutla , Nick Cercone, Privacy intrusion detection using dynamic Bayesian networks, Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet, August 13-16, 2006, Fredericton, New Brunswick, Canada [doi>10.1145/1151454.1151493]
	3	Yudistira Asnar , Paolo Giorgini , Fabio Massacci , Nicola Zannone, From Trust to Dependability through Risk Analysis, Proceedings of the The Second International Conference on Availability, Reliability and Security, p.19-26, April 10-13, 2007 [doi>10.1109/ARES.2007.93]
	4	Applied Computer Security Associates. Workshop on. In Information Security System Scoring and Ranking, 2001.
	5	P. Balzarotti, M. Monga, and S. Sicari. Assessing the risk of using vulnerable components. In Proceedings of the 2nd ACM workshop on Quality of protection, 2005.
	6	Thomas Beth , Malte Borcherding , Birgit Klein, Valuation of Trust in Open Networks, Proceedings of the Third European Symposium on Research in Computer Security, p.3-18, November 07-09, 1994
	7	Common vulnerability scoring system - SIG. available at: http://www.first.org/cvss/, Accessed May 2008.
	8	M. Frigault and L. Wang. Measuring network security using bayesian network-based attack graphs. In Proceedings of the 3rd IEEE International Workshop on Security, Trust, and Privacy for Software Applications (STPSA'08), 2008.
	9	Klaus Havelund , Grigore Roşu, Efficient monitoring of safety properties, International Journal on Software Tools for Technology Transfer (STTT), v.6 n.2, p.158-173, August 2004 [doi>10.1007/s10009-003-0117-6]
	10	K. S. Hoo. Metrics of network security. White Paper, 2004.
	11	S. Jajodia, S. Noel, and B. O'Berry. Topological analysis of network attack vulnerability. In V. Kumar, J. Srivastava, and A. Lazarevic, editors, Managing Cyber Threats: Issues, Approaches and Challenges. Kluwer Academic Publisher, 2003.
	12	Andrew Jaquith, Security Metrics: Replacing Fear, Uncertainty, and Doubt, Addison-Wesley Professional, 2007
	13	Y. Liu and H. Man. Network vulnerability assessment using bayesian networks. In Proceedings of SPIE - Data Mining, Intrusion Detection, Information Assurance and Data Networks Security (SPIE'05), pages 61--71, 2005.
	14	Pratyusa Manadhata , Jeannette Wing , Mark Flynn , Miles McQueen, Measuring the attack surfaces of two FTP daemons, Proceedings of the 2nd ACM workshop on Quality of protection, October 30-30, 2006, Alexandria, Virginia, USA [doi>10.1145/1179494.1179497]
	15	John McHugh, Quality of protection: measuring the unmeasurable?, Proceedings of the 2nd ACM workshop on Quality of protection, p.1-2, October 30-30, 2006, Alexandria, Virginia, USA [doi>10.1145/1179494.1179495]
	16	V. Mihajlovic and M Petkovic. Dynamic bayesian networks: A state of the art. available at: http://doc.utwente.nl/36632/1/0000006a.pdf.
	17	National Institute of Standards and Technology. Technology assessment: Methods for measuring the level of computer security. NIST Special Publication 500--133, 1985.
	18	National vulnerability database. available at: http://www.nvd.org, May 9, 2008.
	19	Joseph Pamula , Sushil Jajodia , Paul Ammann , Vipin Swarup, A weakest-adversary security metric for network configuration security analysis, Proceedings of the 2nd ACM workshop on Quality of protection, October 30-30, 2006, Alexandria, Virginia, USA [doi>10.1145/1179494.1179502]
	20	Michael K. Reiter , Stuart G. Stubblebine, Authentication metric analysis and design, ACM Transactions on Information and System Security (TISSEC), v.2 n.2, p.138-158, May 1999 [doi>10.1145/317087.317088]
	21	Ronald W. Ritchey , Paul Ammann, Using Model Checking to Analyze Network Vulnerabilities, Proceedings of the 2000 IEEE Symposium on Security and Privacy, p.156, May 14-17, 2000
	22	Oleg Sheyner , Joshua Haines , Somesh Jha , Richard Lippmann , Jeannette M. Wing, Automated Generation and Analysis of Attack Graphs, Proceedings of the 2002 IEEE Symposium on Security and Privacy, p.273, May 12-15, 2002
	23	M. Swanson, N. Bartol, J. Sabato, J. Hash, and L. Graffo. Security metrics guide for information technology systems. NIST Special Publication 800--55, 2003.
	24	Lingyu Wang , Tania Islam , Tao Long , Anoop Singhal , Sushil Jajodia, An Attack Graph-Based Probabilistic Security Metric, Proceeedings of the 22nd annual IFIP WG 11.3 working conference on Data and Applications Security, July 13-16, 2008, London, UK [doi>10.1007/978-3-540-70567-3_22]
	25	Lingyu Wang , Steven Noel , Sushil Jajodia, Minimum-cost network hardening using attack graphs, Computer Communications, v.29 n.18, p.3812-3824, November, 2006 [doi>10.1016/j.comcom.2006.06.018]
	26	Lingyu Wang , Anoop Singhal , Sushil Jajodia, Toward measuring network security using attack graphs, Proceedings of the 2007 ACM workshop on Quality of protection, October 29-29, 2007, Alexandria, Virginia, USA [doi>10.1145/1314257.1314273]
	27	L. Wang, A. Singhal, and S. Jajodia. Measuring the overall security of network configurations using attack graphs. In Proceedings of 21th IFIP WG 11.3 Working Conference on Data and Applications Security (DBSEC'07), 2007.
	28	L. Wang, C. Yao, A. Singhal, and S. Jajodia. Interactive analysis of attack graphs using relational queries. In Proceedings of 20th IFIP WG 11.3 Working Conference on Data and Applications Security (DBSEC'06), pages 119--132, 2006.