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Quantifying Security in Secure Software Development Phases

Authors: Muhammad Umair Ahmed Khan; Mohammad Zulkernine;

Quantifying Security in Secure Software Development Phases

Abstract

Secure software is crucial in todaypsilas software dependent world. However, most of the time, security is not addressed from the very beginning of a software development life cycle (SDLC), and it is only incorporated after the software has been developed. Even when security is considered since the inception of the software development, there is no concrete way to quantify security of an SDLC artifact. This quantification is necessary to know about the security state of an SDLC artifact after each phase of software development. Moreover, this could help the software developers in allocating further resources to increase security and decrease the vulnerabilities in any software. In this paper, we use vulnerability occurrences to calculate a vulnerability index of an SDLC artifact that provides an indication about the existing vulnerabilities. Moreover, we calculate a security index by using the combined potential damage that can be caused due to vulnerabilities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Average
Top 10%
Top 10%
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