The connected nature of devices within the Internet of Things (IoT) has ushered in unprecedented opportunities, as well as formidable challenges in ensuring robust cybersecurity. This edited book presents research and insights into practice that explore the current patterns, difficulties, and effective solutions for IoT cybersecurity.
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.
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 DevicesA
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
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.
