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ABSTRACT
A security metric measures or assesses the extent to which a system meets its security objectives. Since meaningful quantitative security metrics are largely unavailable, the security community primarily uses qualitative metrics for security. In this paper, we present a novel quantitative metric for the security of computer networks that is based on an analysis of attack graphs. The metric measures the security strength of a network in terms of the strength of the weakest adversary who can successfully penetrate the network. We present an algorithm that computes the minimal sets of required initial attributes for the weakest adversary to possess in order to successfully compromise a network; given a specific network configuration, set of known exploits, a specific goal state, and an attacker class (represented by a set of all initial attacker attributes). We also demonstrate, by example, that diverse network configurations are not always beneficial for network security in terms of penetrability.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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1
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2
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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]
|
| |
3
|
Applied Computer Security Associates. Workshop on Information Security System Scoring and Ranking, 2001.
|
| |
4
|
Common Vulnerabilities & Exposures (CVE). The standard for information security vulnerability names. http://cve.mitre.org.
|
| |
5
|
|
| |
6
|
Marc Dacier. Towards Quantitative Evaluation of Computer Security. PhD thesis, Institut National Polytechnique de Toulouse, 1994.
|
| |
7
|
M. Howard, J. Pincus, and J. M. Wing. Measuring relative attack surfaces. In Proceedings of the Workshop on Advanced Developments in Software and Systems Security, August 2003.
|
| |
8
|
S. Jajodia, S. Noel, and B. O'Berry. Topological analysis of network attack vulnerability. In Managing Cyber Threats: Issues, Approaches and Challenges, pages 248--266. V. Kumar, J. Srivastava and A. Lazarevic (Eds.), Springer-Verlag, 2005.
|
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9
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|
| |
10
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S. Jha, O. Sheyner, and J. M. Wing. Minimization and reliability analysis of attack graphs. Technical Report CMU-CS-02-109, School of Computer Science, Carnegie Mellon University, February 2002.
|
| |
11
|
National Institute of Standards and Technology. Security Metrics Guide for Information Technology Systems, number 800-55 in NIST Special Publication, 2003.
|
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12
|
|
| |
13
|
|
 |
14
|
|
| |
15
|
|
| |
16
|
|
| |
17
|
Oleg Sheyner and Jeannette Wing. Tools for generating and analyzing attack graphs. In Proceedings of International Symposium on Formal Methods for Components and Objects, Lecture Notes in Computer Science 3188, pages 344--371, 2004.
|
| |
18
|
V. Swarup, S. Jajodia, and J. Pamula. Rule-based topological vulnerability analysis. In Proceedings of the 3rd International Workshop on Mathematical Methods, Models, and Architectures for Computer Network Security (MMM-ACNS 2005), pages 23--37, St. Petersburg, Russia, September 2005.
|
| |
19
|
L. Swiler, C. Phillips, D. Ellis, , and S. Chakerian. Computer-attack graph generation tool. In Proceedings of the DARPA Information Survivability Conference & Exposition II (DISCEX '01), pages 307--321, June 2001.
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CITED BY 5
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Marcel Frigault , Lingyu Wang , Anoop Singhal , Sushil Jajodia, Measuring network security using dynamic bayesian network, Proceedings of the 4th ACM workshop on Quality of protection, October 27-27, 2008, Alexandria, Virginia, USA
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Nwokedi C. Idika , Brandeis H. Marshall , Bharat K. Bhargava, Maximizing network security given a limited budget, The Fifth Richard Tapia Celebration of Diversity in Computing Conference: Intellect, Initiatives, Insight, and Innovations, April 01-04, 2009, Portland, Oregon
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