A Comprehensive Analysis of AI-Enhanced DevSecOps in Strengthening Distributed Systems Security and Compliance

This research examines how artificial intelligence enhances vulnerability management within DevSecOps practices and its quantifiable impact on distributed systems security posture across industries. Through analysis of empirical studies and industry implementations from 2019-2024, we found that organizations implementing AI-enhanced vulnerability management achieved 96% correlation between prioritized vulnerabilities and actual exploits (versus 59% with traditional methods), remediated 3.7 times more critical vulnerabilities within the same timeframe, and reduced vulnerability exposure time by 46%. The research establishes a measurement framework for vulnerability management improvements and provides evidence-based recommendations for implementing AI-enhanced approaches in distributed architectures. Key success factors include shift-left integration, contextual vulnerability analysis, and predictive vulnerability management capabilities, with notable applications in critical sectors such as healthcare and information technology.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-15
DOI
https://doi.org/10.32628/cseit25112449
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

A Comprehensive Analysis of AI-Enhanced DevSecOps in Strengthening Distributed Systems Security and Compliance

Kalyan Chakravarthy Thatikonda
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Big Data and Business Intelligence
article

A Comprehensive Analysis of AI-Enhanced DevSecOps in Strengthening Distributed Systems Security and Compliance

Kalyan Chakravarthy Thatikonda
article en

Abstract

This research examines how artificial intelligence enhances vulnerability management within DevSecOps practices and its quantifiable impact on distributed systems security posture across industries. Through analysis of empirical studies and industry implementations from 2019-2024, we found that organizations implementing AI-enhanced vulnerability management achieved 96% correlation between prioritized vulnerabilities and actual exploits (versus 59% with traditional methods), remediated 3.7 times more critical vulnerabilities within the same timeframe, and reduced vulnerability exposure time by 46%. The research establishes a measurement framework for vulnerability management improvements and provides evidence-based recommendations for implementing AI-enhanced approaches in distributed architectures. Key success factors include shift-left integration, contextual vulnerability analysis, and predictive vulnerability management capabilities, with notable applications in critical sectors such as healthcare and information technology.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Salesforce (United States) (US)
Openalex Percentile: Top 93%
Big Data and Business Intelligence
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