Artificial Intelligence and Data Mining Approaches in Security Frameworks : Advances and Challenges

Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts.

Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to artificial intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalized security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and data mining and several other computing technologies to deploy such a system in an effective manner.

This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice.

This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.

This groundbreaking new volume:

• Clarifies the understanding of certain key mechanisms of technology helpful in the use of artificial intelligence and data mining in security frameworks
• Covers practical approaches to the problems engineers face in working in this field, focusing on the applications used every day
• Contains numerous examples, offering critical solutions to engineers and scientists
• Presents these new applications of AI and data mining that are of prime importance to human civilization as a whole

Neeraj Bhargava, PhD, is a professor and head of the Department of Computer Science at Maharshi Dayanand Saraswati University in Ajmer, India, having earned his doctorate from the University of Rajasthan, Jaipur in India. He has over 30 years of teaching experience at the university level and has contributed to numerous books throughout his career. He has also published over 100 papers in scientific and technical journals and has been an organizing chair on over 15 scientific conferences. His work on face recognition and fingerprint recognition is often cited in other research and is well-known all over the world.

Ritu Bhargava, PhD, is an assistant professor in the Department of Computer Science at Sophia Girls College in Ajmer, India, having earned her PhD in computer science from Hemchandracharya North Gujarat University Patan, Gujarat, India. She has more than 15 years of active teaching and research experience and has contributed to three books and more than 30 papers in scientific and technical journals. She has also been an organizing chair on over 15 scientific conferences, and, like her colleague, her work on face recognition and fingerprint recognition is well-known and often cited.

Pramod Singh Rathore, MTech, is an assistant professor at the Aryabhatta College of Engineering and Research Center and visiting faculty member at MDSU in Ajmer, India. He is a PhD in computer science and engineering at the University of Engineering and Management and already has eight years of teaching experience and over 45 papers in scientific and technical journals. He has also co-authored and edited numerous books.

Rashmi Agrawal, PhD, is a professor in the Department of Computer Applications at the Manav Rachna International Institude of Research and Studies in Faridabad, India with more than 18 years of teaching experience. She is a book series editor and the associate editor on a scientific journal on data science and the internet of things. She has published many research papers in scientific and technical journals in these areas and contributed multiple chapters to numerous books. She is currently guiding PhD students and is an active reviewer and editorial board member of various journals.