Static Analysis Frameworks for Scalable Taint Tracking in Micro-Services FinTech Systems
Keywords:
Static Analysis, Taint Tracking, Micro-Services, FinTech Security, Dataflow Analysis, PCI DSS, GDPR, Program Analysis, Interprocedural Analysis, Secure Software EngineeringAbstract
The decomposition of monolithic financial software into micro-service architectureshas dramatically expanded the data-flow attack surface of fintech platforms, introducingcomplex inter-service taint propagation paths that conventional static analysis tools are ill equipped to track at scale
References
: Mayank Atreya, Navin Chhibber, Harvendra Singh, Explainable Machine Learning For Dynamic Pricing In Fast-Changing Retail Environments, 2022/4/9, Journal ,Available at SSRN 6011354, https://scholar.google.com/citations?view_op=view_citation&hl=en&user=fyViF1UAAAAJ&citation_for_view=fyViF1UAAAAJ:LkGwnXOMwfcC.
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Published
2024-08-15
How to Cite
Kaleshwar Aryasomayajula. (2024). Static Analysis Frameworks for Scalable Taint Tracking in Micro-Services FinTech Systems. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 8994–9007. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5610
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