This book presents AI-driven approaches for combating spam, phishing, and malware in email systems. It reviews classical techniques, identifies their limitations, and introduces two novel frameworks-FLIDA and G-SFO with adaptive capsule networks. It also highlights the role of quantum machine learning in enabling scalable and resilient email security.Key Features: Concise review of classical and AI-based spam detection. Innovative frameworks: FLIDA and G-SFO-ACapsNet. Insights into quantum paradigms for cybersecurity. Empirical evaluations and comparative performance analyses. Open research issues and future perspectives. This is a valuable resource for researchers, postgraduate students, and professionals in cybersecurity, AI, and data science, as well as industry practitioners and policymakers working on secure communication technologies.

This book presents AI-driven approaches for combating spam, phishing, and malware in email systems. It reviews classical techniques, identifies their limitations, and introduces two novel frameworks-FLIDA and G-SFO with adaptive capsule networks. It also highlights the role of quantum machine learning in enabling scalable and resilient email security.Key Features: Concise review of classical and AI-based spam detection. Innovative frameworks: FLIDA and G-SFO-ACapsNet. Insights into quantum paradigms for cybersecurity. Empirical evaluations and comparative performance analyses. Open research issues and future perspectives. This is a valuable resource for researchers, postgraduate students, and professionals in cybersecurity, AI, and data science, as well as industry practitioners and policymakers working on secure communication technologies.

This book presents AI-driven approaches for combating spam, phishing, and malware in email systems. It reviews classical techniques, identifies their limitations, and introduces two novel frameworks-FLIDA and G-SFO with adaptive capsule networks. It also highlights the role of quantum machine learning in enabling scalable and resilient email security.Key Features: Concise review of classical and AI-based spam detection. Innovative frameworks: FLIDA and G-SFO-ACapsNet. Insights into quantum paradigms for cybersecurity. Empirical evaluations and comparative performance analyses. Open research issues and future perspectives. This is a valuable resource for researchers, postgraduate students, and professionals in cybersecurity, AI, and data science, as well as industry practitioners and policymakers working on secure communication technologies.