What type of study is this?

This is a Mixed-Methods study (also classified as: Systematic Review, Quantitative Study).

September 29, 2025Open Access

Secure Software Engineering: A Synthesis of SSDLC, Devsecops, and Ai-Driven Threat Mitigation

Key Points

Organizations using SSDLC and DevSecOps report a measurable reduction in system vulnerabilities.
Empirical results show that security-first frameworks enhance incident response times, indicating improved effectiveness.
Adopting emerging technologies like artificial intelligence supports proactive vulnerability detection, driving better security practices.
A comprehensive review emphasizes the need for security integration in software engineering to protect user data and system integrity.

Abstract

This study explores the critical convergence of software development and cybersecurity through a mixed-method approach combining systematic literature review, quantitative analysis, and case study evaluation to investigate the effectiveness of secure software development practices. As cyber threats grow in sophistication, traditional software engineering models prioritizing functionality and efficiency have proven inadequate in addressing evolving security challenges. The incorporation of Secure Software Development Lifecycle (SSDLC) and DevSecOps methodologies has emerged as a pivotal strategy, embedding security considerations from the earliest phases of development. This paper provides a comprehensive review of secure software development practices, core cybersecurity principles, regulatory compliance requirements, and technological innovations driving this integration. Drawing on insights from academic research, industry reports, and real-world applications, the findings emphasize the effectiveness of security-centric development paradigms, such as SSDLC and DevSecOps, in mitigating risks and strengthening software resilience. Furthermore, emerging technologies like artificial intelligence, blockchain, and automated security testing are reshaping secure development strategies by enabling predictive analytics, dynamic access control, and proactive vulnerability detection. Empirical results indicate that organizations adopting security-first frameworks report measurable reductions in system vulnerabilities and enhanced response times to incidents. This study underscores the imperative of embedding security within software engineering processes to ensure robust application design, safeguard user data, maintain system integrity, and reinforce the broader digital ecosystem. The findings offer valuable guidance for software developers, cybersecurity professionals, and organizational leaders seeking to enhance the security posture and long-term resilience of their software systems

Secure Software Engineering: A Synthesis of SSDLC, Devsecops, and Ai-Driven Threat Mitigation

Key Points

Abstract

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