The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Model-based Security Metrics Using ADversary VIew Security Evaluation (ADVISE)
Abstract
System architects need quantitative security metrics to make informed trade-off decisions involving system security. The security metrics need to provide insight on weak points in the system defense, considering characteristics of both the system and its adversaries. To provide such metrics, we formally define the ADversary View Security Evaluation (ADVISE) method. Our approach is to create an executable state-based security model of a system and an adversary that represents how the adversary is likely to attack the system and the results of such an attack. The attack decision function uses information about adversary attack preferences and possible attacks against the system to mimic how the adversary selects the most attractive next attack step. The adversary's decision involves looking ahead some number of attack steps. System architects can use ADVISE to compare the security strength of system architecture variants and analyze the threats posed by different adversaries. We demonstrate the feasibility and benefits of ADVISE using a case study. To produce quantitative model-based security metrics, we have implemented the ADVISE method in a tool that facilitates user input of system and adversary data and automatically generates executable models.
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“There are though several proposals (Henry and Haimes, 2009; LeMay et al., 2011; McQueen et al., 2006; Patel et al., 2008), which we mark with regarding risk evaluation in Table 7, where the comparison of risk metrics is performed between differ-ent security configurations of a system.”
From A review of cyber security risk assessment methods for SCADA systems (2016) · cites this paper as LeMay et al., 2011
Citations
Cites
Guide to Industrial Control Systems (ICS) Security
Stouffer, K., Pillitteri, V., Lightman, S., Abrams, M., & Hahn, A. (2015) · doi:10.6028/nist.sp.800-82r2 · Cited by 1,377
Automated generation and analysis of attack graphs
Sheyner, O., Haines, J., Jha, S., Lippmann, R., & Wing, J. M. (2005) · Proceedings 2002 IEEE Symposium on Security and Privacy · doi:10.1109/secpri.2002.1004377 · Cited by 1,293
Secrets and lies: digital security in a networked world
(2001) · Choice Reviews Online · doi:10.5860/choice.38-3941 · Cited by 1,159
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Ortalo, R., Deswarte, Y., & Kaaniche, M. (1999) · IEEE Transactions on Software Engineering · doi:10.1109/32.815323 · Cited by 404
Practical Attack Graph Generation for Network Defense
Ingols, K., Lippmann, R., & Piwowarski, K. (2006) · 2006 22nd Annual Computer Security Applications Conference (ACSAC'06) · doi:10.1109/acsac.2006.39 · Cited by 379
Guide to Industrial control Systems (ICS) security :
Stouffer, K. A., Falco, J. A., & Scarfone, K. A. (2008) · doi:10.6028/nist.sp.800-82e2008 · Cited by 369
The Mobius framework and its implementation
Deavours, D. D., Clark, G., Courtney, T., Daly, D., Derisavi, S., Doyle, J. M., Sanders, W. H., & Webster, P. G. (2002) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2002.1041052 · Cited by 275
Self-citationSecrets and Lies: Digital Security in a Networked World
(2003) · info · doi:10.1108/info.2003.5.1.78.4 · Cited by 189
Scenario graphs and attack graphs
Sheyner, O., & Wing, J. M. (2004) · Defense Technical Information Center (DTIC) · Cited by 175
Toward measuring network security using attack graphs
Wang, L., Singhal, A., & Jajodia, S. (2007) · doi:10.1145/1314257.1314273 · Cited by 127
Research works printed but not linked: 1
- whiteman, 2008, Network Risk Assessment Tool (NRAT), The Iaido Newsletter, 11, 4
Cited by
A review of cyber security risk assessment methods for SCADA systems
Cherdantseva, Y., Burnap, P., Blyth, A., Eden, P., Jones, K., Soulsby, H., & Stoddart, K. (2016) · Computers & Security · doi:10.1016/j.cose.2015.09.009 · Cited by 606
A survey of cyber security management in industrial control systems
Knowles, W., Prince, D., Hutchison, D., Disso, J. F. P., & Jones, K. (2015) · International Journal of Critical Infrastructure Protection · doi:10.1016/j.ijcip.2015.02.002 · Cited by 344
A Survey on Systems Security Metrics
Pendleton, M., Garcia-Lebron, R., Cho, J.-H., & Xu, S. (2017) · ACM Computing Surveys · doi:10.1145/3005714 · Cited by 283
Metadata
- Authors
- LeMay, E., Ford, M. D., Keefe, K., Sanders, W. H., & Muehrcke, C.
- Venue
- 2011 Eighth International Conference on Quantitative Evaluation of SysTems
- Publisher
- IEEE
- Published
- 2011-09
- Pages
- 191-200
- Cited by
- 128
- References
- 15
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- LeMay, E., Ford, M. D., Keefe, K., Sanders, W. H., & Muehrcke, C. (2011). Model-based Security Metrics Using ADversary VIew Security Evaluation (ADVISE). 2011 Eighth International Conference on Quantitative Evaluation of SysTems. https://doi.org/10.1109/qest.2011.34
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
