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• W2949151944 abstract "Having a precise vulnerability discovery model (VDM) would provide a useful quantitative insight to assess software security. Thus far, several models have been proposed with some evidence supporting their goodness-of-fit. In this work we describe an independent validation of the applicability of six existing VDMs in seventeen releases of the three popular browsers Firefox, Google Chrome and Internet Explorer. We have collected five different kinds of data sets based on different definitions of a vulnerability. We introduce two quantitative metrics, goodness-of-fit entropy and goodness-of-fit quality, to analyze the impact of vulnerability data sets to the stability as well as quality of VDMs in the software life cycles. The experiment result shows that the confirmed-by-vendors' advisories data sets apparently yields more stable and better results for VDMs. And the performance of the s-shape logistic model (AML) seems to be superior performance in overall. Meanwhile, Anderson thermodynamic model (AT) is indeed not suitable for modeling the vulnerability discovery process. This means that the discovery process of vulnerabilities and normal bugs are different because the interests of people in finding security vulnerabilities are more than finding normal programming bugs." @default.
• W2949151944 created "2019-06-27" @default.
• W2949151944 creator A5042262297 @default.
• W2949151944 creator A5085639552 @default.
• W2949151944 date "2012-03-26" @default.
• W2949151944 modified "2023-09-25" @default.
• W2949151944 title "An Independent Validation of Vulnerability Discovery Models" @default.
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• W2949151944 hasPublicationYear "2012" @default.
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