Modern Approaches in Iot and Machine Learning for Cyber Security: Latest Trends in Ai - Couverture rigide

Couverture rigide

ISBN 10 : 3031099540 ISBN 13 : 9783031099540

Editeur : Springer International Publishing AG, 2023

Synopsis

This book examines the cyber risks associated with Internet of Things (IoT) and highlights the cyber security capabilities that IoT platforms must have in order to address those cyber risks effectively. The chapters fuse together deep cyber security expertise with artificial intelligence (AI), machine learning, and advanced analytics tools, which allows readers to evaluate, emulate, outpace, and eliminate threats in real time. The book's chapters are written by experts of IoT and machine learning to help examine the computer-based crimes of the next decade. They highlight on automated processes for analyzing cyber frauds in the current systems and predict what is on the horizon. This book is applicable for researchers and professionals in cyber security, AI, and IoT.

A propos du livre

À propos de l?auteur

Vinit Kumar Gunjan, Dean of Academics and Associate Professor in Department of Computer Science & Engineering at CMR Institute of Technology Hyderabad (Affiliated to Jawaharlal Nehru Technological University, Hyderabad). An active researcher; published research papers in IEEE, Elsevier & Springer Conferences, authored several books and edited volumes of Springer series, most of which are indexed in SCOPUS database. Awarded with the prestigious Early Career Research Award in the year 2016 by Science Engineering Research Board,

Department of Science & Technology Government of India. Senior Member of IEEE, An active Volunteer of IEEE Hyderabad section; volunteered in the capacity of Treasurer, Secretary & Chairman of IEEE Young Professionals Affinity Group & IEEE Computer Society. Was involved as organizer in many technical & non-technical workshops, seminars & conferences of IEEE & Springer. During the tenure I had an honour of working with top leaders of IEEE and awarded with best IEEE Young Professional award in 2017 by IEEE Hyderabad Section.

Mohd Dilshad Ansari is currently working as Associate Professor in the Department of Computer Science & Engineering at SRM University Delhi-NCR, Sonepat, Haryana, India. He received B.Tech in Information Technology from Uttar Pradesh Technical University, Lucknow, UP in 2009. He received his M.Tech and Ph.D. in Computer Science & Engineering from Jaypee University of Information Technology, Waknaghat, Solan, HP, India in 2011 and 2018 respectively. He has more than 8 years of Academic/ Research Experience and published more than 30 papers in International Journals (SCIE/Scopus), conferences (IEEE/Springer). He is the Member of various Technical/Professional societies such as IEEE, UACEE and IACSIT. He has been appointed as Editorial/Reviewer Board and Technical Programme Committee member in various reputed Journals/Conferences. He is also Guest Editor of Special Issues from Reputed Journals and Organized Special Sessions in IEEE/Springer Conferences. His research interest includes Digital & Fuzzy Image Processing, Machine Learning, IoT and Cloud Computing.

Mohammed Usman received B.E in Electronics and Communications from Madras University, India in 2002. He received his M.Sc and PhD from University of Strathclyde, UK in 2003 and 2008 respectively. He is the recipient of the University scholarship from Strathclyde for his PhD. He has more than a decade of experience in academics and academic administration. He is a senior member of IEEE and IEEE Communications Society. He has been TPC chair and organizing chair for IEEE conferences and actively involved in IEEE activities. He is currently working as Assistant Professor in the department of Electrical Engineering at King Khalid University, Saudi Arabia. He received the & academic excellence' award from the College of Engineering at King Khalid University and also received the award for best project in 2016. A senior design project under his supervision received the talent and innovation award in 2018.His research is focused on technologies for next generation wireless networks, signal processing for biomedical application, probabilistic modeling and channel coding.

Nguyen ThiDieuLinh, Ph.D. is working in the Division of Electronics and Telecommunication Engineering in Electronics and Information, Faculty of Electronics Engineering Technology, Hanoi University of Industry, Vietnam (HaUI). Currently She is heading the department since 2015. She has more than 17 years of academic experience in electronics, IoT, Smart Garden and telecommunication. She has authored or co-authored more than 15 research articles that are published injournals, books and conference proceedings. .She teaches graduate & post graduate level courses at HaUI, Viet Nam. She received Ph.D in Information and Communication Engineering from Harbin Institute of Technology, Harbin, China in 2013; Master of Electronic Engineering from Le Quy Don Technical University, Hanoi, Vietnam in 2006 and Bachelor of Electronic Engineering from HCMC University of Technology and Education, Vietnam in 2004. She is an editor for "Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches" and "Distributed Artificial Intelligence: A Modern Approach" publisher by Taylor & Francis Group, LLC, USA. She is also board member with International Journal of Hyperconnectivity and the Internet of Things (IJHIoT) IGI-Global, USA, Information Technology Journal, Mobile Networks and Application Journal and some other reputed journal and international conferences.

Détails de l'édition

• Éditeur: Springer International Publishing AG
• Date d'édition: 2023
• Langue: anglais
• ISBN 10: 3031099540
• ISBN 13: 9783031099540
• Reliure: Relié
• Nombre de pages: 417
• Éditeur: Gunjan Vinit Kumar, Ansari Mohd Dilshad, Usman Mohammed, Nguyen ThiDieuLinh
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne