THE ROLE OF AI IN CYBERSECURITY: A STUDY ON THE INTEGRATION OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN CYBERSECURITY
Keywords:
Machine Learning, Artificial Intelligence In Cybersecurity, Threat Detection, Adversarial Attacks, Explainable AIAbstract
The rapid evolution of cyber threats has necessitated the integration of Artificial Intelligence (AI) and Machine Learning (ML) into cybersecurity frameworks. This paper examines the technical, operational, and ethical dimensions of AI-driven cybersecurity systems, emphasizing their applications in threat detection, vulnerability management, and adaptive defense mechanisms. By analyzing advancements in supervised, unsupervised, and deep learning models, the study highlights their efficacy in mitigating zero-day attacks, phishing campaigns, and network intrusions. Challenges such as adversarial attacks, algorithmic bias, and regulatory compliance are critically assessed, supported by empirical data and industry benchmarks. The paper concludes with forward-looking recommendations for leveraging emerging technologies like federated learning and quantum-resistant algorithms to fortify global cybersecurity infrastructures.
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