The Role of Machine Learning in Cybersecurity Practice: A Narrative Review

Abstract: The rising complexity of cyber threats, consisting of AI-generated phishing and polymorphic malware, has outpaced the skills of traditional signature-based safety structures, exposing essential vulnerabilities in modern-day virtual infrastructure. This assessment significantly examines and synthesizes 24 peer-reviewed research posted between 2014 and 2024 to evaluate the transformative function of system getting to know (ML) in bridging this cybersecurity gap. The evaluation indicates that ML provides adaptive, actual-time defense mechanisms, improving accuracy in intrusion detection, malware classification, and phishing prevention. notwithstanding these advantages, demanding situations remain, such as restrained datasets, susceptibility to antagonistic attacks, and the opaque “black container” nature of complicated models, which constrain sensible deployment. The look at concludes that ML is an critical foundation for destiny cybersecurity, yet its complete capacity relies upon on studies targeted on Explainable AI (XAI), hostile resilience, and efficient set of rules layout. almost, these findings underscore the significance of interdisciplinary collaboration to translate ML-pushed intelligence from theoretical frameworks into powerful, resilient, and trustworthy cybersecurity structures. Keywords: Machine Learning; Cybersecurity; Intrusion Detection; Adversarial Attacks; Explainable AI (XAI); Threat Detection. Title: The Role of Machine Learning in Cybersecurity Practice: A Narrative Review Author: Ifteker Hossen Rakib, Md Sumon Prodhan International Journal of Novel Research in Computer Science and Software Engineering ISSN 2394-7314 Vol. 12, Issue 2, May 2025 - August 2025 Page No: 65-71 Novelty Journals Website: www.noveltyjournals.com Published Date: 25-August-2025 DOI: https://doi.org/10.5281/zenodo.16939724 Paper Download Link (Source) https://www.noveltyjournals.com/upload/paper/The%20Role%20of%20Machine%20Learning-25082025-1.pdf