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Vulnerability diffusions in software product networks

Authors
Kang, MartinTempleton, GaryUm, SungYong
Issue Date
Dec-2023
Publisher
Elsevier BV
Keywords
diffusion of software vulnerability; digital resources; information security; machine learning; network theory; Node2Vec; software vulnerability
Citation
Journal of Operations Management, v.69, no.8, pp 1342 - 1370
Pages
29
Indexed
SCIE
SSCI
SCOPUS
Journal Title
Journal of Operations Management
Volume
69
Number
8
Start Page
1342
End Page
1370
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/118936
DOI
10.1002/joom.1270
ISSN
0272-6963
1873-1317
Abstract
During software product development, the combination of digital resources (such as application programming interfaces and software development kits) establishes loose and tight edges between nodes, which form a software product network (SPN). These edges serve as observable conduits that may help practitioners and researchers better understand how vulnerabilities diffuse through SPNs. We apply network theory to analyze data from over 12 years of records extracted from the National Vulnerability Database. We contribute novel measures established using machine learning to gauge the properties influencing vulnerability diffusion within an SPN. We observed an SPN having a discernable shape that changed over time via network updates. We propose hypotheses and find empirical evidence that vulnerability diffusion is influenced by edge dynamics, developer responses, and their interaction. Implications for practice are that increased developer responses reduce software vulnerability diffusion attributed to edge dynamics.
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