Surjeet Dalal

Exploring the field of generative artificial intelligence (GenAI) and its use in the processing and security of multimedia content, this co-authored book addresses the critical needs and emerging challenges in the rapidly evolving intersection of artificial intelligence, multimedia content, and cybersecurity. The capabilities of sophisticated GenAI models in generating, improving, and manipulating multimedia information, including images, videos, and audio are thoroughly explored. Coverage also extends to technical innovations including advanced neural network topologies, novel training methods, and methods for boosting GenAI-generated content quality and authenticity. The book's focus on security and privacy concerns and the weaknesses brought on by GenAI includes data privacy challenges, the development of unlicensed material, and the exploitation of AI for nefarious intentions. Furthermore, the ethical implications and legal obstacles involved in guaranteeing the secure and accountable implementation of generative AI in multimedia applications are examined and potential future directions identified. Generative AI for Multimedia Content Processing, Security and Privacy: Fundamentals, advances and applications will be a useful reference for multimedia researchers and engineers working with GenAI, particularly those interested in security and privacy challenges. Cybersecurity researchers and engineers working on digital content security and synthetic media prevention, AI researchers and engineering and technology practitioners developing generative AI technologies, will all find relevant information in this volume. The book will also be of interest to regulatory and compliance experts, policy makers and regulators working on AI deployment and data protection; and digital rights and intellectual property specialists.

Cloud computing technology has gained immense popularity in the recent years. It is the new word that describes an internet based computing technology which enables the users to access information and use various resources from the clouds from any location. This technology is evolving and developing with the increasing demands in the IT Sector and business environments. In this book the issue of load balancing in cloud environment is taken. A load balancing algorithm is developed using the genetic algorithm concept which is based on the evolutionary mechanism. On the basis of two parameters, response time and overall cost, a genetic algorithm is developed to balance the workload efficiently in cloud computing environment. The results illustrated the improvement in the response time and overall cost of the cloud system