AI-Powered Cybersecurity: The Future of Threat Detection

Abstract

Abstract - This paper explores the transformative role of Artificial Intelligence (AI) in cybersecurity, focusing on its ability to enhance threat detection, automate responses, and mitigate evolving cyber threats. Traditional cybersecurity measures, reliant on predefined rules and signature-based detection, struggle to combat advanced threats like polymorphic malware and zero-day exploits. AI-powered solutions leverage machine learning, deep learning, and behavioral analytics to proactively identify and neutralize threats in real time. Key advantages include reduced human error, scalability, and predictive threat intelligence. However, challenges such as adversarial AI attacks, data privacy concerns, and ethical biases must be addressed. The study highlights real-world applications, emerging trends like Explainable AI (XAI), and the integration of AI with quantum computing. By analyzing current advancements and future prospects, this research underscores AI’s critical role in shaping the future of cybersecurity. Key Words: artificial Intelligence, Machine Learning, cybersecurity, Threat Detection, Intrusion Detection Systems (IDS), Anomaly Detection, Network Security,