Muhammad Imam | Searcharxiv

arXiv2025

Comparative Analysis of AI-Driven Security Approaches in DevSecOps: Challenges, Solutions, and Future Directions

The integration of security within DevOps, known as DevSecOps, has gained traction in modern software development to address security vulnerabilities while maintaining agility. Artificial Intelligence (AI) and Machine Learning (ML) have been increasingly leveraged to enhance security automation, threat detection, and compliance enforcement. However, existing studies primarily focus on individual aspects of AI-driven security in DevSecOps, lacking a structured comparison of methodologies. This study conducts a systematic literature review (SLR) to analyze and compare AI-driven security solutions in DevSecOps, evaluating their technical capabilities, implementation challenges, and operational impacts. The findings reveal gaps in empirical validation, scalability, and integration of AI in security automation. The study highlights best practices, identifies research gaps, and proposes future directions for optimizing AI-based security frameworks in DevSecOps.

cs.CR↗

arXiv2020

Taxonomy and Practical Evaluation of Primality Testing Algorithms

Many modern asymmetric encryption methods rely on prime numbers, as they have distinctive properties. For instance, the security of RSA cryptosystem relies on the computational difficulty of factoring a large composite number in its prime factors, a problem that remains challenging for classical computers but potentially solvable using quantum algorithms. On the other hand, generating large prime numbers is also challenging due to their irregular distribution among integers, necessitating the use of primality testing algorithms to verify candidate primes. In this paper, we intensively review and classify various classical and quantum algorithms for factorization and primality testing, highlighting their advantages, limitations, speed/accuracy tradeoffs, time complexities, along with a brief summary. Furthermore, we apply and compare these algorithms to gain practical insights and conduct a comprehensive performance comparison. The insights from this paper show that while quantum factoring algorithms, particularly Shor's algorithm and its refinements, have introduced significant advancements over their classical counterparts, quantum primality testing algorithms have not demonstrated comparable advantages.

cs.CR↗