AI-DRIVEN CYBERSECURITY: HOW MACHINE LEARNING DETECTS AND PREVENTS HACKING ATTEMPTS

Abstract

With the rapid growth of digital technologies, cyber threats have become more frequent, complex, and sophisticated. Traditional cybersecurity methods based on predefined rules and signatures are no longer sufficient to protect modern information systems. Artificial Intelligence (AI), particularly Machine Learning (ML), has emerged as a powerful tool for enhancing cybersecurity by enabling systems to detect, analyze, and prevent hacking attempts in real time. This article explores the role of AI-driven cybersecurity, focusing on how machine learning techniques are used to identify malicious activities, predict cyberattacks, and strengthen digital defense mechanisms. Various machine learning models, detection approaches, and practical applications are discussed, along with current challenges and future prospects. The study highlights the importance of AI-based solutions in building resilient and adaptive cybersecurity systems.