Vulnerability Discovery Model
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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
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- ↑ a b 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.
- ↑ E. Rescola, “Is finding security holes a good idea?,” Security and Privacy, pp. 14–19, Jan./Feb. 2005.
- ↑ 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.
- ↑ 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.
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