The critical intersection of AI and next-generation wireless communication is essential in safeguarding digital infrastructure. As wireless networks grow more complex, the need for robust and adaptive security solutions has never been greater. AI offers the potential to detect threats in optimizing network performance and respond dynamically to evolving cyber risks. Intelligent algorithms can be integrated into wireless architectures to create resilient, self-healing systems that not only enhance connectivity but also ensure their trustworthiness in an increasingly connected world. Ensuring Secure Connectivity Through AI-Powered Wireless Systems explores the role of AI in enhancing security and sustainability within modern wireless communication systems. This book provides cutting-edge research and real-world applications of AI in wireless systems. Covering topics such as AI, wireless systems, and security, this book is an excellent resource for graduate students, academicians, researchers, security professionals, policymakers, and more.
Mehta, Shilpa: - Shilpa Mehta has completed her PhD degree from Auckland University of Technology, New Zealand. She has five years of teaching experience from different reputed colleges and universities of India. She has also worked as a Teaching Assistant at Auckland University of Technology (AUT), Auckland, New Zealand. Currently, she is working as an independent researcher. She was awarded Summer Doctoral Research Scholarship for her PhD research. She has worked on various interdisciplinary research projects and her research interests include Radio Frequency Integrated Circuits, RF front ends, Optimization, Internet of Things, Wireless Communication, Artificial Intelligence, Healthcare, Radars, and Software-defined Radios, Smart Cities. As an editor, she has edited four books with IGI Global and one with Nova Science Publishers. She is also working on different edited books to be published by IGI Global, Apple Academic Press, Scrivener-Wiley, Cambridge, and Springer Nature, respectively.
Pandey, Hari Mohan: - Hari Mohan Pandey works in data science and artificial intelligence at school of technology Bournemouth University, UK. They are featured in the 2022 World Ranking list of Top 2% scientist by Sandford University. They specialized in Computer Science & Engineering. My research area includes artificial intelligence, soft computing techniques, natural language processing, language acquisition, machine learning, deep learning and computer vision. They have been an author of various books in computer science engineering (algorithms, programming and evolutionary algorithms). Recently, my book entitle "State of the Art on Grammatical Inference Using Evolutionary Method " has been published in Elsevier. They have published over 120 scientific papers in reputed journals and conferences. They are serving on the editorial board of reputed journals (including Neural Networks Elsevier, Applied Soft Computing Elsevier, Swarm and Evolutionary Computing Elsevier, Neural Computing and Applications Springer, IEEE Transactions of Evolutionary Computation, IEEE Transactions on Industrial Informatics, Neurocomputing Springer, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Neural Networks and Learning Systems and Knowledge Based Systems Elsevier) as action editor, associate editor, and guest editor. They are a reviewer of top international conferences such as GECCO, CEC, IJCNN, BMVC, AAAI etc. They have delivered expert talks as keynote and invited speaker. They are a fellow of the HEA of the UK Professional Standards Framework (UKPSF) and have a rich teaching experience at the higher education level. They have delivered lecturers in the International summer/winter schools. I have been given the prestigious award "The Global Award for the Best Computer Science Faculty of the Year 2015", award for completing INDO-US project "GENTLE", award (Certificate of Exceptionalism) from the Prime Minister of India and award for developing innovative teaching and learning models for higher-education. In past, They worked as a sr. lecturer in computer science department at Edge Hill University. They also worked as a research fellow machine learning at the school of technology at Middlesex University London where they worked on a European Commission project- DREAM4CARS. My role was to research and develop advanced machine learning techniques relevant to the project goals and to evaluate these on both project & reference data sets. To lead and manage relevant work packages in support of the project, ensuring appropriate interfacing with partners.
