Role of Artificial Intelligence in Cybersecurity: A Survey

Abstract

The integration of Artificial Intelligence (AI) into cybersecurity has revolutionized the field, providing advanced capabilities to combat the rising sophistication of cyber threats. This paper explores the pivotal role of AI in modern cybersecurity, presenting a comprehensive review of traditional approaches and their limitations, followed by an analysis of key AI methodologies such as machine learning (ML), deep learning (DL), and natural language processing (NLP). These methodologies are highlighted for their transformative applications, including real-time threat detection, network security, fraud prevention, and vulnerability assessment. The paper also delves into the technical challenges and ethical considerations associated with implementing AI in cybersecurity, including data privacy concerns, adversarial attacks, and bias in algorithms. Furthermore, emerging trends such as explainable AI, federated learning, and quantum-resistant cryptography are discussed as future directions, emphasizing the need for interdisciplinary collaboration to address evolving cyber threats. By synthesizing insights from over 70 academic references and real-world case studies, this review underscores AI's potential to shape a safer digital future while highlighting areas requiring further research and ethical scrutiny. This work serves as a foundational resource for academics, industry professionals, and policymakers aiming to leverage AI for enhanced cybersecurity resilience