AI-DRIVEN THREAT DETECTION AND RESPONSE: A PARADIGM SHIFT IN CYBERSECURITY

Abstract

The research paper delves into the transformative role of artificial intelligence (AI) in revolutionizing cybersecurity. This study examines the historical context and evolution of AI in the cybersecurity landscape, emphasizing its significance and scope. The literature review scrutinizes traditional threat detection methods, AI-driven models, and identifies gaps in current research. Theoretical foundations elucidate AI and machine learning concepts, while the methodology outlines research design, data sources, AI algorithms, and evaluation metrics. The paper explores AI's role in threat detection and response, encompassing machine learning models and incident response workflows. Challenges encompass ethical considerations, technological limitations, biases, and potential vulnerabilities in AI models. Future directions highlight emerging trends and offer recommendations for further research. Ultimately, this paper underscores the pivotal shift AI brings to cybersecurity, addressing threats and shaping the future of defense mechanisms.