Detecting And Preventing Cyber Threats In Real-Time Using AI

Authors: Urvashi Makwana, Pooja Joshi, Riya Makwana, Shubham Kashyap, Dr. Sumit Soni

Abstract: The rapid digitalization of industries, financial systems, and critical infrastructure has significantly increased exposure to sophisticated cyber threats. Traditional security mechanisms, including rule-based intrusion detection systems and static firewalls, are wholly insufficient to combat modern, adaptive adversaries. Artificial Intelligence (AI), leveraging machine learning (ML), deep learning (DL), natural language processing (NLP), and behavioral analytics, has emerged as a transformative paradigm for detecting and preventing cyber threats in real time. This paper comprehensively explores AI's role in cybersecurity, presenting a novel architecture model, a detailed threat detection flowchart, practical case studies, current technical challenges, and forward-looking research directions. Results from existing literature confirm that AI-based systems consistently outperform traditional approaches, achieving detection accuracies exceeding 95% against known and novel attack vectors.

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