Synergies in Data Analytics and Cyber Security

This book presents the select proceedings of the 7th International Conference on Data Analytics and Cyber Security (DACS 2024). It covers distinct features of various data analytics, cyber security, and synergies in data analytics and cyber security to resolve physical world problems. The book will be useful for researchers and professionals interested in the broad field of cyber security.

Bridges the gap between data analytics and cybersecurity for integrated defense strategies Covers real-world case studies to demonstrate practical applications and outcomes Explores emerging technologies and trends shaping the future of secure data analysis

Autorentext

Deepak Puthal is an award-winning researcher and is well known internationally for his contributions to research in Cyber Security, Blockchain, Edge Computing, and the Internet of Things. His groundbreaking contributions in these areas have garnered him numerous prestigious international accolades. He is currently a faculty member at Khalifa University, UAE, and before this, he was an assistant professor at Newcastle University, UK. Dr. Puthal has received his Ph.D. from the Faculty of Engineering and IT, University of Technology Sydney (UTS), Australia, and is currently an honorary fellow at UTS.
Bijaya Ketan Panigrahi has been working as a professor in the Department of Electrical Engineering since 2005 and was the founder head of Centre for Automotive Research and Tribology (CART) at the Indian Institute of Technology (IIT), New Delhi, India. His research focus is the design and development of artificial intelligence-based tools for power system planning, operation, control, management protection and security. Primarily his research contributions are in the domain of detection and classification of power quality events, fault diagnostics of induction motor drives, diagnostics of electric vehicle motors. He has investigated intelligent techniques for the design of maximum power point tracking controller for the solar photovoltaic system. Prof. Panigrahi is also extensively working on energy management in smart grid, EV charging infrastructures, impact of fast charging on the grid, EV battery technology and Battery Management Systems. He has published more than 750 research articles in various international journals and conference proceedings. He is a fellow of IEEE, Indian National Academy of Engineering (INAE) , National Academy of Sciences, India (NASI), and Asia-Pacific Artificial Intelligence Association (AAIA).
Niranjan K. Ray received his PhD from National Institute of Technology, Rourkela, India. He is an Associate Professor of the School of Computer Engineering at the Kalinga Institute of Industrial Technology (KIIT-DU), India, where he teaches for undergraduate and post-graduate courses. He has 3 books and over 75 published papers and four patents. He has received the IEEE Outstanding Service Award for 2022 from IEEE Computer Society, Bio-inspired Computing STC. His main research interests are Internet of Things, Edge/Fog Computing, sensor and ad hoc network. He is senior member of IEEE and secretary of Odisha IT Society, India.
Zhiguo Ding received his B.Engg. in Electrical Engineering from the Beijing University of Posts and Telecommunications in 2000, and the Ph.D degree in Electrical Engineering from Imperial College London in 2005. He is currently a Professor in Communications at University of Manchester and Khalifa University. Dr Ding's research interests are machine learning, B5G networks, cooperative and energy harvesting networks and statistical signal processing. He is serving as an Area Editor for the IEEE TWC and OJ-COMS, an Editor for IEEE TVT, COMST, and OJ-SP, and was an Editor for IEEE TCOM, IEEE WCL, IEEE CL and WCMC.

Inhalt

Personalised Multi-Task Federated Learning for Diabetic Retinopathy Medical Image Classification.- Prediction and Analysis of GNSS Broadcast Parameter using Explainable AI.- Privacy and Security in Recommender Systems: A Comprehensive Review, Enhanced Quantum Cryptography with Single Particle State Rotation.- Real-Time Personalization of E-Commerce Recommendations using Graph Neural Networks.- EnML-LrXgRf: An Ensemble Technique for Prognosticating Diabetes Mellitus.- Analyzing the factors in a smart campus using Fuzzy Best and worst method with Borda Aggregation.- Cryptanalysis of some Lattice-based Blind Signatures.-Etc