AI-Powered Cybersecurity: Advancing Threat Detection and Prevention with Machine Learning

Abstract

The cyber threats become increasingly sophisticated and pervasive, traditional security mechanisms are often inadequate to detect and prevent emerging attacks. This paper explores the transformative role of artificial intelligence (AI), particularly machine learning (ML), in enhancing cybersecurity defenses. The machine learning (ML) algorithms can analyze vast amounts of data in real time to identify patterns, detect anomalies, and predict potential threats with high accuracy. The Significant applications such as intrusion detection systems, malware classification, phishing detection, and behavioral analytics are highlighted. The study also addresses the challenges associated with implementing AI in cybersecurity, including data privacy concerns, adversarial attacks, and model interpretability. Ultimately, the underscores that AI-powered solutions represent a crucial advancement in proactive threat detection and adaptive defense mechanisms, setting a new standard for cybersecurity in an increasingly digital world.