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Vulnerability Discovery Models for a Software System Using Stochastic Differential Equations

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  • Romuald Hoffmann

    (Wojskowa Akademia Techniczna w Warszawie)

Abstract

Vulnerability discovery models (VDMs) illustrate changes in the vulnerability detection processes of software during system lifecycles. So far very few VDMs based on stochastic differential equations have been proposed. In this paper, there were presented two vulnerability discovery models based on Itô-type stochastic differential equations. The first was the Alhazmi-Malaiya Logistic Model based on the stochastic differential equation proposed by Shrivastava, Sharma and Kapur in 2015. The second one, proposed in this paper, was a modified Rescorla Exponential Model using the Itô stochastic differential equation. The proposed modified Rescorla model was obtained by using the stochastic differential equation approach to the Goel-Okumoto software reliability model.

Suggested Citation

  • Romuald Hoffmann, 2017. "Vulnerability Discovery Models for a Software System Using Stochastic Differential Equations," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 45, pages 177-188.
    • Handle: RePEc:sgh:annals:i:45:y:2017:p:177-188
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    References listed on IDEAS

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    1. P.K. Kapur & Hoang Pham & A. Gupta & P.C. Jha, 2011. "Software Reliability Assessment with OR Applications," Springer Series in Reliability Engineering, Springer, number 978-0-85729-204-9, March.
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