AI-Driven Threat Detection and Automated Response System for Proactive Cybersecurity Defense

Abstract

The introduction of AI-Enhanced Cyber Threat Detection, which aids in improving organizational security through sophisticated algorithms, has caused a paradigm shift in cybersecurity. This research explores the proactive approach of AI-driven detection systems that autonomously analyze massive datasets to identify patterns indicative of cyber intrusions and attacks. These tools alleviate the workload of human analysts by automating routine tasks like threat identification and incident response, enabling human experts to focus on higher-level decision-making. AI-driven systems also provide real-time network monitoring, boosting operational efficiency and reducing dwell time. Further, this paper discusses the integration of AI with threat intelligence platforms and SOAR systems. However, challenges like adversarial attacks and ethical considerations persist, requiring ongoing research and collaboration to strengthen AI-powered cyber threat identification. This paper underscores the need for proactive defense strategies and joint cybersecurity measures to safeguard digital assets in the face of modern e-crimes.