Research in IoT/IIoT/OT Attacks and Defenses
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".
Deadline for manuscript submissions: 15 January 2025 | Viewed by 155
Special Issue Editors
2. Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
Interests: anomaly detection; artificial narrow intelligence; intrusion detection evaluation
Interests: DFP (Design For Power) and DFM (Design for Manufacturing) for ultra-low-power VLSI chip design and automation; circuit design for nanometer scaled devices such as carbon nanotube FETs
Special Issues, Collections and Topics in MDPI journals
Interests: in-vehicle network security; industrial control system security; digital forensics; anomaly detection algorithm
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In an era marked by the rapid expansion of the Internet of Things (IoT), Industrial Internet of Things (IIoT), and Operational Technology (OT) systems, the cybersecurity landscape has evolved significantly. These advancements have heightened the importance of robust cybersecurity measures as the complexity and frequency of attacks continue to escalate. This Special Issue seeks to explore cutting-edge research in the realm of attacks and defenses within industrial cybersecurity, focusing particularly on the most recent innovations in intrusion detection and the application of machine learning and artificial intelligence.
Our aim is to curate a collection of articles that not only address software-based approaches but also delve into hardware-based solutions, thereby providing a holistic view of the current technological defenses. Contributors are encouraged to present studies related to the development and enhancement of intrusion detection systems, leveraging both conventional and novel methodologies. Additionally, this issue intends to highlight research on the creation and utilization of effective datasets that are critical for evaluating cybersecurity mechanisms in industrial environments.
By bringing together research that covers a broad spectrum of technologies and approaches—from neural networks and deep learning models that predict and mitigate attacks, to the design of hardware components that enhance security at the physical level—this Special Issue will serve as a vital resource for researchers and practitioners alike. We welcome submissions that offer theoretical insights, empirical research, case studies, and reviews that advance the understanding of IoT/IIoT/OT cybersecurity.
This issue will provide a platform for researchers to share insights, foster collaboration, and advance the field of industrial cybersecurity, ensuring a safer technological future.
Dr. Jake Cho
Prof. Dr. Ken Choi
Prof. Dr. Taeshik Shon
Guest Editors
Manuscript Submission Information
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Keywords
- smart device security
- advanced IIoT protocols
- cyber-physical system protection
- AI-driven threat detection
- deep learning for security
- blockchain in cybersecurity
- edge computing security
- synthetic data for security testing
- adaptive security architecture
- next-gen intrusion prevention systems
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