IoT Cybersecurity (Advances in Computational Collective Intelligence)

ISBN 10: 1032958782 / ISBN 13: 9781032958781

Published by Auerbach Publications, 2026

About this Item

Seller Inventory # I-9781032958781

Bibliographic Details

• Title: IoT Cybersecurity (Advances in Computational Collective Intelligence)
• Publisher: Auerbach Publications
• Publication Date: 2026
• Language: English
• ISBN 10: 1032958782
• ISBN 13: 9781032958781
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Internet of Things (IoT) systems create a massive attack surface with billions of connected devices that often have weak default credentials and limited security capabilities, making them easy targets for cybercriminals to exploit at scale. Compromised IoT devices can serve as entry points for attackers to access valuable network resources, steal sensitive personal and business data, or launch large‑scale botnet attacks that disrupt critical infrastructure. Without proper security measures, IoT vulnerabilities can lead to serious consequences, including operational disruptions, safety hazards in critical systems like healthcare and transportation, and significant financial and legal penalties from regulatory noncompliance. IoT Cybersecurity: Trends, Challenges, and Solutions addresses the significant knowledge gap between rapidly deployed connected devices and understanding their unique security challenges. Highlights include:

• An efficient lightweight cryptography technique for enhancing IoT security
• Machine learning approaches for IoT network threat detection and security optimization
• Using AI to enhance IoT-based intrusion detection systems
• A study on emerging threats and vulnerabilities

This book presents research and insights into practice that explore security holes and effective solutions in the realm of IoT cybersecurity. Covering the evolving threat landscape in IoT environments, it sheds light on the intricacies of cybersecurity patterns and addresses the challenges that arise. This book is a resource offering innovative solutions, research findings, case studies, and practical insights related to securing IoT ecosystems.

About the Author

Dr. Laxmi Shaw is a senior postdoctoral fellow in the Dell Medical School at the University of Texas at Austin. Her primary research interests encompass pattern recognition, cognitive and neuroscience, IoT-based cloud computing, computer vision, and machine learning.

Dr. D. Ajitha is an associate professor in School of Computer Science and Engineering, Vellore Institute of Technology, India.

Dr. Chinmay Chakraborty is an associate professor and head of the Centre of Innovation & Research (COIR) in Medical Technology at KIIT (Deemed to be University), India.

Dr. S.M. Prabin is an assistant professor, Snior Grade, in the Department of Computer Science and Engineering, Vellore Institute of Technology, India.