The future policing ought to cover the identification of new assaults, the disclosure of new ill-disposed patterns and forecast of any future vindictive patters from the accessible authentic information. Such keen information will bring about building clever advanced proof handling frameworks that will help cops investigate violations. Artificial Intelligence for Cyber Defence and Smart Policing will describe the best way of practising artificial intelligence for cyber defence and smart policing. Key Features: • Combines both AI for cyber defence and smart policing in one place • Covers novel strategies in future to help cybercrime examinations and police. • Discusses different AI models to fabricate more exact techniques • Elaborates on problematization and international issues. • Includes case studies and real-life examples. This book is primarily aimed at graduates, researchers and IT professionals. Business executives will also find this book helpful. S Vijayalakshmi is currently working as an Associate Professor in the Data Science Department in CHRIST (Deemed to be University), Pune, Lavasa Campus. She is having many academic portfolios associated with the current position. Her research area is on Image Processing and IoT. P Durgadevi is working as an Assistant Professor in the department of Computer Science and Engineering, GITAM University, Bengaluru. Her research interest is in medical image processing, Machine Learning and IoT. Lija Jacob is an Assistant Professor at the Dept. of Data Science, Christ [Deemed to be University],Pune Lavasa. She has more than 17 years of teaching experience and 8 years of research experience. Her research interests are Computer Vision, Machine learning, Deep Learning, etc. Balamurugan Balusamy is currently working as Professor in the School of Computing Sciences and Engineering at Galgotias University, Greater Noida, India. He has published 30+ books on various technologies and visited 15 plus countries for his technical course. He has several top-notch conferences in his resume and has published over 150 of quality journal, conference and book chapters combined.

The book is a monograph in the cross disciplinary area of Computational Intelligence in Finance and elucidates a collection of practical and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results using MATLAB implementations, over live portfolios invested across global stock universes. The book has been structured in such a way that, even novices in finance or metaheuristics should be able to comprehend and work on the hybrid models discussed in the book.