Artificial Intelligence In Cybersecurity: A Comprehensive Survey

The rapid growth of digital technologies and interconnected systems has greatly increased the complexity and scale of cyber threats. Traditional cybersecurity methods, which depend on predefined rules and signature-based detection, often have difficulty identifying advanced, dynamic, and new attacks. In this situation, artificial intelligence has emerged as a powerful tool for improving cybersecurity by enabling smart, flexible, and automated defence systems. This research offers a thorough look at how artificial intelligence is used in cybersecurity, focusing on machine learning, deep learning, and anomaly detection techniques for identifying and responding to threats. The study reviews current security methods, examines their weaknesses, and discusses how AI-driven approaches enhance detection accuracy, lower false positives, and support proactive security management. An AI-based cybersecurity framework is also presented to show how smart models can work with security monitoring, data processing, and automated response features. The effectiveness of AI-based cybersecurity solutions is assessed through performance analysis and discussions of experimental results, highlighting improvements in real-time threat detection and system efficiency. Additionally, the research explores important application areas, challenges, and future directions, including explainable artificial intelligence, privacy-preserving learning, and autonomous security operations. Overall, this study emphasizes the important role of artificial intelligence in strengthening modern cybersecurity systems and underscores its potential to tackle evolving cyber threats through ongoing learning and smart decision-making.