This book covers the fundamental concepts of private AI and its applications. It also covers fusion of Private AI with cutting-edge technologies like cloud computing, federated learning and computer vision.

Security Models and Applications for Sustainable Development Using Private AI reviews various encryption algorithms used for providing security in private AI. It discusses the role of training machine learning and Deep learning technologies in private AI. The book provides case studies of using private AI in various application areas such as purchasing, education, entertainment, medical diagnosis, predictive care, conversational personal assistants, wellness apps, early disease detection, and recommendation systems. The authors provide additional knowledge to handling the customer's data securely and efficiently. It also provides multi-model dataset storage approaches along with the traditional approaches like anonymization of data and differential privacy mechanisms.

The target audience includes undergraduate and postgraduate students in Computer Science, Information technology, Electronics and Communication Engineering and related disciplines. This book is also a one stop reference point for professionals, security researchers, scholars, various government agencies and security practitioners, and experts working in the cybersecurity Industry specifically in the R & D division.

Autorentext

Uma Maheswari V is Senior Member of IEEE and working as an Associate Professor, Department of CSE, Chaitanya Bharathi Institute of Technology, Hyderabad, India.

Rajanikanth Aluvalu is a Senior Member of IEEE and working as Director and Professor, Symbiosis Institute of Technology, Hyderabad Campus, Hyderabad, Symbiosis International (Deemed University), Pune, India. Post Doctoral Research Fellow, COPE labs, Lusófona University, Portugal, Member, Artificial Intelligence Group, Department of Computer Engineering, Lusófona University, Portugal.