Organisations are increasingly using artificial intelligence (AI) to strengthen their cybersecurity defences, especially against phishing attempts and intrusion detection, as cyber threats continue to change. A significant development in this field is represented by AI-powered supervised classifiers, which utilize vast amounts of data to enhance detection accuracy and response times. This study investigates the use of AI-driven supervised classifiers in big data settings, emphasising how well they can detect intrusions in real time and identify and mitigate phishing risks.
This study investigates AI-based threat detection methods, assesses their efficacy in cybersecurity, and discusses the moral ramifications of AI-powered security solutions. Future cybersecurity frameworks can improve resilience against cyber threats and guarantee strong digital protection in a period of growing cyber hazards by combining AI with blockchain technology, quantum computing, and federated learning.