UiTM PROFESSORIAL LECTURE: CYBERSECURITY, BIG DATA, AND ARTIFICIAL INTELLIGENCE

In this concise book, | synthesise my foundational research at the critical nexus of cybersecurity, big data, and artificial intelligence to provide both a historical overview and a forward-looking blueprint for secure, intelligent systems. By tracing the evolution of my work, from autonomous Intrusion Response Systems (IRS) and reversible cryptographic watermarking in healthcare to the pioneering Single-Round, Privacy-Preserving Federated Learning (PraFL) Paradigm, and advanced spatiotemporal predictive modelling for marine environments, this publication demonstrates how the exponential scale of massive datasets can be securely harnessed to train powerful Al models without compromising user privacy. Ultimately, this compilation serves as a concentrated, high-impact guide for researchers, practitioners, and policymakers, illustrating that the future of resilient technological infrastructure relies on the inseparable integration of advanced machine learning capabilities with uncompromising, mathematically sound cryptographic safeguards.