Cybersecurity Issues in the Internet of Things

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 September 2024 | Viewed by 1199

Special Issue Editors


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Guest Editor
Department of Information Management, National Taiwan University of Science and Technology, 43 Keelung Rd., Sect. 4, Taipei 106, Taiwan
Interests: IoT/IoV security; blockchain security; zero trust architecture; user privacy; trusted computing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Information Management, National Taiwan University of Science and Technology, 43 Keelung Rd., Sect. 4, Taipei 106, Taiwan
Interests: information and communication security; applied cryptology; secure protocol design; security management
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Management, National Taiwan University of Science and Technology, 43 Keelung Rd., Sect. 4, Taipei 106, Taiwan
Interests: machine learning; data mining; digital transformation; financial technology

Special Issue Information

Dear Colleagues,

As the Internet of Things expands, the need for robust cybersecurity measures becomes increasingly critical. This Special Issue aims to explore and address these IoT security challenges.

Our focus areas include AI-assisted trustworthy architecture examining how artificial intelligence can enhance security through generating new trust models in IoT systems, cyber security analytics for IoT Applications looking at how data analytics can help detect and prevent cyber threats in IoT, and information privacy, a crucial aspect given the vast amount of data generated by IoT devices.

This issue will also delve into machine learning security for IoT applications, exploring how machine learning can enhance IoT security, and secure protocol design focusing on developing secure communication protocols for IoT systems.

Other important research topics for IoT systems include device identity and authentication, access control and management, and API security, all of which are fundamental to maintaining the integrity and security of IoT applications.

Finally, we are interested in exploring how zero trust architecture, a security model that assumes no trust and verifies everything, could be realized in IoT environments.

We invite researchers and practitioners to contribute their valuable insights and join us in advancing the field of IoT cybersecurity.

Papers on, but not limited to, the following topics are welcome:

  1. IoT Security
  2. AI-assisted Trust-worthy Architecture in IoT Environments
  3. Cyber Security Analytics for IoT Applications
  4. Information Privacy and Data Privacy in IoT Environments
  5. Machine Learning Security for IoT Applications
  6. Secure Protocol Design for IoT Environments
  7. Device Identity and Authentication for IoT Systems
  8. Access Control and Management for IoT Systems
  9. API Security for IoT Applications
  10. Zero Trust Architecture in IoT Environments

Prof. Dr. Nai-Wei Lo
Dr. Jheng-Jia Huang
Dr. Chih-Chieh Chang
Guest Editors

Manuscript Submission Information

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Keywords

  • IoT security
  • AI-assisted secure IoT mechanism
  • zero trust architecture for IoT

Published Papers (2 papers)

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Research

22 pages, 4289 KiB  
Article
Formal Analysis and Detection for ROS2 Communication Security Vulnerability
by Shuo Yang, Jian Guo and Xue Rui
Electronics 2024, 13(9), 1762; https://doi.org/10.3390/electronics13091762 - 2 May 2024
Viewed by 416
Abstract
Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 (Robot Operating System [...] Read more.
Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 (Robot Operating System 2) can directly affect the security of the upper-level robotic systems. Therefore, it is a worthwhile research topic to detect and analyze the security of ROS2. In this study, we adopted a formal approach to analyze the security of the communication mechanism of ROS2. First, we used a state transition system to model the potential vulnerabilities of ROS2 based on the ROS2 communication mechanism and the basic process of penetration testing. Secondly, we introduced a CIA model based on the established vulnerability model and used linear temporal logic to define its security properties. Then, we designed and implemented a vulnerability detection tool for ROS2 applications based on the vulnerability model and security properties. Finally, we experimentally tested some ROS2-based applications, and the results show that ROS2 has vulnerabilities without additional protection safeguards. Full article
(This article belongs to the Special Issue Cybersecurity Issues in the Internet of Things)
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26 pages, 9322 KiB  
Article
DCGFuzz: An Embedded Firmware Security Analysis Method with Dynamically Co-Directional Guidance Fuzzing
by Yunzhi Wang and Yufeng Li
Electronics 2024, 13(8), 1433; https://doi.org/10.3390/electronics13081433 - 10 Apr 2024
Viewed by 598
Abstract
Microcontroller Units (MCUs) play a vital role in embedded devices due to their energy efficiency and scalability. The firmware in MCUs contains vulnerabilities that can lead to digital and physical harm. However, testing MCU firmware faces challenges due to various tool limitations and [...] Read more.
Microcontroller Units (MCUs) play a vital role in embedded devices due to their energy efficiency and scalability. The firmware in MCUs contains vulnerabilities that can lead to digital and physical harm. However, testing MCU firmware faces challenges due to various tool limitations and unavailable firmware details. To address this problem, research is turning to fuzzing and rehosting. Due to the inherent imbalance in computational resources of the fuzzing algorithm and the lack of consideration for the computational resource requirements of rehosting methods, some hardware behavior-related paths are difficult to discover. In this work, we propose a novel Dynamically Co-directional Guidance Fuzzing (DCGFuzz) method to improve security analysis efficiency. Our method dynamically correlates computational resource allocation in both fuzzing and rehosting, computing a unified power schedule score. Using the power schedule score, we adjust test frequencies for various paths, boosting testing efficiency and aiding in the detection of hardware-related paths. We evaluated our approach on nine real-world pieces of firmware. Compared to the previous approach, we achieved a maximum increase of 47.9% in path coverage and an enhancement of 27.6% in effective model coverage during the fuzzing process within 24 h. Full article
(This article belongs to the Special Issue Cybersecurity Issues in the Internet of Things)
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