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词条 Vulnerability Discovery Model
释义

  1. See also

  2. References

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 [https://gitlab.com/reubenajohnston/mcmcBayes 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

{{Portal|Computer security}}
  • Attack (computing)
  • Computer security
  • Information security
  • IT risk
  • Threat (computer)
  • Vulnerability (computing)

References

1. ^{{cite thesis |type=PhD |last=Johnston |first=Reuben |date=August 31, 2018 | title=A Multivariate Bayesian Approach to Modeling Vulnerability Discovery in the Software Security Lifecycle |publisher=The George Washington University}}
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. ^{{Cite journal|last=Anand|first=Adarsh|last2=Bhatt|first2=Navneet|date=2016-05-12|title=Vulnerability Discovery Modeling and Weighted Criteria Based Ranking|journal=Journal of the Indian Society for Probability and Statistics|language=en|volume=17|issue=1|pages=1–10|doi=10.1007/s41096-016-0006-4|issn=2364-9569}}
7. ^{{Cite web|url=http://www.ijmems.in/assets/22-ijmems-si-vol.-2,-no.-4,-288%E2%80%93299,-2017.pdf|title=VDM|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=}}
8. ^{{Cite journal |author=Johnston|display-authors=etal | title=Bayesian-model averaging using MCMCBayes for web-browser vulnerability discovery | journal=Reliability Engineering & System Safety | volume=183 | date=March 2019 | pages=341–359 | doi=10.1016/j.ress.2018.11.030}}
9. ^{{Cite journal |author=Johnston|display-authors=etal | title=Multivariate models using MCMCBayes for web-browser vulnerability discovery | journal=Reliability Engineering & System Safety | volume=176 | date=August 2018 | pages=52–61 | doi=10.1016/j.ress.2018.03.024}}

2 : Computer security|System software
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