Ai-based Metaheuristics for Information Security and Digital Media

This book examines the latest developments in Artificial Intelligence (AI)-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications. Drawing on multidisciplinary research including computer vision, machine learning, artificial intelligence, and modified/newly developed metaheuristics algorithms, it will enhance information security for society. It includes state-of-the-art research with illustrations and exercises throughout.

Dr Apoorva S Shastri is a Research Assistant Professor at Artificial Intelligence at the MITWPU, Pune, India. Her research interests include optimization algorithms, VLSI design, multi-objective optimization, continuous, discrete and combinatorial optimization, complex systems, manufacturing and self-organizing systems. She has developed socio-inspired optimization methodologies such as Multi-Cohort Intelligence Algorithm and Expectation Algorithm.

Dr Mangal Singh is an Associate Professor at Symbiosis Institute of Technology, Symbiosis International (Deemed University). His main research interests are the development and application of optimization heuristics algorithms and their applications to various engineering fields. He is also working on signal processing for 6G and beyond wireless communication.

Dr Anand J Kulkarni is working as Professor and Associate Director of the Institute of Artificial Intelligence at the MITWPU, Pune, India. His research interests include optimization algorithms, multi-objective optimization, continuous, discrete and combinatorial optimization, swarm optimization and self-organizing systems.

Dr Patrick Siarry is a Professor in automatics and informatics. His main research interests are the development of new stochastic global optimization heuristics and their applications to various engineering fields. He is also interested in the fitting of process models to experimental data, the learning of fuzzy rule bases and of neural networks.