Vulnerability Discovery Model

A Vulnerability Discovery Model (VDM) uses discovery event data with software reliability models for predicting the same. A thorough presentation of VDM techniques is available in.[1] Numerous model implementations are available in the MCMCBayes open source repository. Several VDM examples include:

* Alhazmi-Malaiya: Time based model (Alhazmi-Malaiya Logistic (AML) model)[2]
* Alhazmi-Malaiya: Effort based model[2]
* Rescorla: Quadratic Model and Exponential Model [3]
* Anderson: Thermodynamic Model[4]
* Kim: Weibull Model[5]
* Linear Model
* Hump-Shaped Model[6]
* Independent and Dependent Model[7]
* Vulnerability Discovery Modeling using Bayesian model averaging[8]
* Multivariate Vulnerability Discovery Models [9]

## See also

* Attack (computing)
* Computer security
* Information security
* IT risk
* Threat (computer)
* Vulnerability (computing)

## References

1. ↑ Johnston, Reuben (August 31, 2018). A Multivariate Bayesian Approach to Modeling Vulnerability Discovery in the Software Security Lifecycle (PhD). The George Washington University.
2. ↑ 2.0 2.1 O. H. Alhazmi and Y. K. Malaiya, “Quantitative vulnerability assessment of systems software,” in Proc. Annual Reliability and Maintainability Symposium, January 2005, pp. 615–620.
3. ↑ E. Rescola, “Is finding security holes a good idea?,” Security and Privacy, pp. 14–19, Jan./Feb. 2005.
4. ↑ R. J. Anderson, “Security in open versus closed systems—The dance of Boltzmann, Coase and Moore,” in Open Source Software: Economics, Law and Policy. Toulouse, France, June 20–21, 2002.
5. ↑ HyunChul Joh, Jinyoo Kim, Yashwant K. Malaiya, "Vulnerability Discovery Modeling Using Weibull Distribution," issre, pp. 299–300, 2008 19th International Symposium on Software Reliability Engineering, 2008.
6. ↑ Anand, Adarsh; Bhatt, Navneet (2016-05-12). "Vulnerability Discovery Modeling and Weighted Criteria Based Ranking" (in en). Journal of the Indian Society for Probability and Statistics 17 (1): 1–10. doi:10.1007/s41096-016-0006-4. ISSN 2364-9569.
7. ↑ "VDM". http://www.ijmems.in/assets/22-ijmems-si-vol.-2,-no.-4,-288–299,-2017.pdf.
8. ↑ Johnston (March 2019). "Bayesian-model averaging using MCMCBayes for web-browser vulnerability discovery". Reliability Engineering & System Safety 183: 341–359. doi:10.1016/j.ress.2018.11.030.
9. ↑ Johnston (August 2018). "Multivariate models using MCMCBayes for web-browser vulnerability discovery". Reliability Engineering & System Safety 176: 52–61. doi:10.1016/j.ress.2018.03.024.

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