IoT Cybersecurity

Trends, Challenges, and Solutions
1. Auflage 2026
ISBN: 978-1-032-95878-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 248 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Advances in Computational Collective Intelligence

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 non-compliance. 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

The 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. The book is a resource offering innovative solutions, research findings, case studies, and practical insights related to securing IoT ecosystems.

Zielgruppe

Postgraduate

Autoren/Hrsg.

Chakraborty, Chinmay

Shaw, Laxmi

Ajitha, D.

Prabin, S. M.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit

Inhaltsverzeichnis

1. An Efficient Lightweight Cryptography Technique for Enhancing IoT Security 2. Enhancement of IoT-Based Intrusion Detection Systems by AI and ML Methodologies 3. Hardware Trojan Vulnerability in IoT End Devices: A Walkthrough 4. Securing the Internet of Things: Proactive Firewalls and the Challenges of Big Data 5. The Human Firewall: Strengthening IoT Security Through Behavior 6. Enhancing IoT Security with Cryptographic Approach 7. Cybersecurity Challenges on the Internet of Things: A Study on Emerging Threats and Vulnerabilities 8. Synergizing Machine Learning and Artificial Intelligence in Internet of Things Environments: Transformative Applications and Future Direction 9. Intelligent Machine Learning Approaches for IoT Network Threat Detection and Security Optimization 10. A Comprehensive Review of AI and IoT-Based Systems for Intelligent Accident Management and Response 11. Navigating the Future of IoT Security: Emerging Trends, Challenges and Strategic Solutions

Über Autor(innen)

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 part of the Electronics & Communication Engineering department at Birla Institute of Technology, India.

Dr. S.M. Prabin is an Assistant Professor Senior Grade in the Department of Computer Science and Engineering at the Vellore Institute of Technology.