Guide to AI for Cybersecurity

Professor Muthu Ramachandran is currently a Cybersecurity, AI, and Blockchain Research Consultant at Forti5 Technologies, UK, and a Professor Extraordinarius at University of South Africa (UNISA). Muthu is a certified IASME CE, ICA, IoT Cyber & IoT Assurance professional with extensive experience spanning academia, industry research, and standards development.Previously, Muthu served as Associate Professor at Leeds Beckett University for 18 years and held visiting professorships at Indian Institute of Technology (ISM) Dhanbad and University of Southampton. His industrial experience includes nearly eight years at Philips Research Labs, Volantis Systems Ltd, and DRDO Hyderabad, working on real-time systems, software architecture, reuse, and testing.Muthu has established several influential Software Engineering Frameworks including Software Security Engineering, Cybersecurity Engineering, AI Ethics and Quality, IoT SE, Cloud SE, and Blockchain in Healthcare. He serves on editorial boards for Blockchain in Healthcare Today (BHTY) and International Journal of Organizational and Collective Intelligence (IJOCI) and has been recognized as a Top Blockchain Voice by LinkedIn.As a Fellow of BCS, Senior Fellow of Advance HE, and Senior Member of IEEE and ACM, Muthu has authored numerous books, book chapters, journal articles, and conference papers. He has chaired and delivered keynote speeches at major conferences including SE-CLOUD, SECE, IoTBDS, and DSC. His research contributions span systems and software engineering, SPI for SMEs, emergency management systems, software components and architectures, software security engineering, and cloud computing.

• .- Introduction..- Modern Threat Landscape and AI Opportunities..- Cybersecurity Frameworks in the AI Era..- AI Security Architecture and Infrastructure..- Machine Learning for Threat Detection..- Advanced Analytics and Threat Intelligence..- Implementation Case Studies..- AI-Enhanced Secure Software Development Lifecycle..- Application Security with Machine Learning..- Data Protection and Privacy in AI Systems..- Automated Incident Response and Orchestration..- AI Security and Adversarial Defences..- Future Directions and Emerging Threats.