An Analytical Security Model for Existing Software Systems

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Date

2014-03-01

Author

Isazadeh, Ayaz
Elgedawy, Islam
Karimpour, Jaber
Izadkhah, Habib

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Nowadays, evaluation of software security, as one of the important quality attributes, is of paramount importance. There are many software systems have not considered security in their design; this makes them vulnerable to security risks. Architecture is the most important consideration in software design that affects final quality of software. Quality attributes such as efficiency and reliability have been studied at software architecture level; however, no report has ever been provided about the effect of software architecture on security. The purpose of this paper is to propose a mathematical-based method for evaluating and quantifying software security using the coupling aspects of the software architecture. To achieve this goal, first, we show the relationship between coupling types and vulnerability using an empirical-based software engineering technique that adopts Mozilla Firefox Browser vulnerability data. Then, we propose a mathematical weighted relationship between coupling types and vulnerability, where regression statistical analysis and Mozilla Firefox vulnerability data are used to predicate the relationship coefficients. Finally, we extract software architecture using DAGC tool and then convert the extracted architecture into Discrete Time Markov chains, which are used to predict and compute the system over all vulnerability.

Subject Keywords

Security, Software Architecture, Mozilla Firefox Browser, Markov chains

URI

https://hdl.handle.net/11511/67692

Journal

APPLIED MATHEMATICS & INFORMATION SCIENCES

DOI

https://doi.org/10.12785/amis/080228

Collections

Engineering, Article

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Citation Formats

A. Isazadeh, I. Elgedawy, J. Karimpour, and H. Izadkhah, “An Analytical Security Model for Existing Software Systems,” APPLIED MATHEMATICS & INFORMATION SCIENCES, pp. 691–702, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67692.