Advances in AI-Based Threat Detection and Response for Modern Cyber security

Author(s)	Ms. Shruti Mulge, Dr. J C Narayana Swamy, Ms. Bhavya K B
Country	India
Abstract	The rapid evolution of cyber threats has driven the need for intelligent and adaptive defense mechanisms, marking a significant shift in cyber security practices. Artificial intelligence (AI)-driven threat detection systems have emerged as a transformative solution, utilizing machine learning, deep learning, and advanced data analytics to identify, analyze, and mitigate threats with high speed and accuracy. Unlike traditional rule-based approaches, AI-enhanced models enable real-time detection of sophisticated attacks, including zero-day exploits and advanced persistent threats (APTs). By continuously learning from dynamic threat data and adapting to evolving attack vectors, these systems significantly improve the robustness and agility of cyber security infrastructures. This paper examines the core technologies underlying AI-based threat detection, evaluates their effectiveness against modern cyber attacks, and highlights their implications for shaping future cyber security strategies.
Keywords	Cyber security, Artificial Intelligence, Machine Learning, Deep Learning, Threat Detection, Advanced Persistent Threats, Zero-Day Exploits.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-12-19
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.62987

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