Artificial Intelligence-Driven Cybersecurity for Multimodal Information

Artificial Intelligence-Driven Cybersecurity for Multimodal Information: Techniques and Applications showcases the potential of integrating artificial intelligence with technologies such as deep learning, quantum techniques, and inspired algorithms to secure data. This book:• Discusses multimedia security through federated learning and highlights the novel aspects of multimodal intelligence through more developed technologies. • Covers techniques such as zero knowledge, post-quantum security, next-generation Internet of Things-driven smart multimedia data and a secure digital twin solution. • Explains artificial intelligence-powered multimedia detection of phishing and social engineering attacks. • Presents edge and cloud-based multimodal data security solutions, explainable and trustworthy artificial intelligence for medical multimedia diagnostics. • Illustrates multimodal fusion and cross-modality threat detection, applications in multimodal cybersecurity, and self-supervised learning for cyber threat detection. The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, cybersecurity, artificial intelligence, machine learning, and information technology.