Security and Privacy in IoT Devices and Computing

Dear Colleagues,

This Special Issue explores the multifaceted security and privacy challenges associated with the Internet of Things (IoT), emphasizing innovative solutions grounded in machine learning, blockchain, and quantum computing. It also examines the role of low-power, low-bandwidth protocols (such as Bluetooth Low Energy (BLE), ZigBee, and Z-Wave) and machine-to-machine communication protocols (such as MQTT and CoAP) in addressing these challenges. The aim of this Special Issue is to present practical and cutting-edge strategies for enhancing IoT security and privacy through a series of case studies, surveys, and original research articles. By focusing on these areas, this Special issue aims to foster collaboration among researchers, practitioners, and stakeholders to tackle the pressing security and privacy issues present in IoT environments.

Focus

The primary focus of this Special Issue is the real-world implications of cyber-attacks on IoT systems and the development of robust solutions to mitigate these risks. Topics include, but are not limited to, device identification, access control, intrusion detection, malware analysis, and software exploitation. This Special Issue also delves into advanced concepts such as lightweight cryptography, quantum-era security solutions, and trust management in IoT.

Scope

The scope of this Special Issue covers a broad range of topics crucial to IoT security and privacy:

• Device fingerprinting and machine learning-based device identification
• Federated learning for enhanced privacy and security
• Blockchain applications for securing IoT systems
• Intrusion detection mechanisms and malware analysis techniques
• Firmware security and third-party firmware evaluation
• Security considerations for narrowband IoT networks
• Methods for detecting zero-day vulnerabilities
• Security measures for communication protocols like BLE, ZigBee, and Z-Wave
• Privacy-enhancing techniques for MQTT and CoAP
• Quantum and post-quantum security solutions
• Security frameworks for IoT-based healthcare and agricultural systems
• Software-defined IoT network security
• Trust management and experimental testbeds for IoT environments
• Government and industry roles in ensuring IoT security
• Case studies highlighting successful and secure IoT deployments

By addressing these diverse topics, this Special Issue not only contributes to the existing literature but also provides actionable insights and solutions to enhance the security and privacy of IoT systems, paving the way for safer and more reliable IoT deployments.

Relationship to Existing Literature

This Special Issue aims to supplement the existing literature by providing comprehensive insights into emerging security and privacy challenges in the IoT landscape. While previous studies have addressed specific aspects of IoT security, this collection seeks to integrate these perspectives into a cohesive framework that addresses both current and future challenges. It builds on established research while introducing novel approaches and technologies, such as federated learning and blockchain, to advance the field. By doing so, it fills gaps in the existing body of knowledge and offers a holistic view of IoT security and privacy, promoting a deeper understanding of this critical area and fostering innovation.

Dr. Saikat Das
Dr. Sajal Saha
Dr. Qudrat E Alahy Ratul
Guest Editors

Manuscript Submission Information

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• Internet of Things
• security and privacy
• machine learning
• intrusion detection
• malware analysis
• block chain
• quantum computing