Cybersecurity in the Next-Generation Industrial Internet of Things Era: Modelling, Detecting and Mitigating Threats
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 28826
Special Issue Editors
Interests: information security; cryptography; machine learning; Internet of Things
Interests: IoT; 5G mobile communication; UAV; quality of service; radio access networks; computer network security; radio networks; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: IoT; 5G and beyond
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; artificial intelligence; intelligent and immersive environments; computer vision
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rise of the Industrial Internet of Things (IIoT) has provided various benefits, such as self-monitoring, pervasive control and self-healing. However, this progression also raises critical cybersecurity and privacy concerns due to the vulnerable nature of legacy and smart IIoT systems. On one hand, legacy IIoT systems, such as industrial control systems (ICS)/supervisory control and data acquisition (SCADA), utilise insecure communication protocols such as Modbus, distributed network protocol (DNP3) and IEC 60870-5-104. Such industrial protocols were designed without considering essential authentication and authorisation mechanisms. On the other hand, smart IIoT entities are subject to a plethora of vulnerabilities and security issues arising from the typical Internet model and the various IIoT technologies. Moreover, IIoT devices handle a vast amount of sensitive data that constitutes an attractive goal for potential cyber attackers. Increasingly, a growing number of advanced persistent threat (APT) groups threaten critical infrastructures (CIs). Both academia and industry have provided valuable countermeasures, such as IEC 62351 recommendations, Artificial Intelligence (AI)-based intrusion detection and prevention systems (IDPS) and security information and event management (SIEM) systems. However, cybersecurity issues against CIs remain a crucial problem. Characteristic examples are the advanced persistent threats (APTs) Dragonfly, Dragonfly 2.0, BlackEnergy 3, TRITON and Operation Wocao. State-of-the-art technologies such as AI, software-defined networking (SDN), network function virtualization (NFV), federated learning (FL) and blockchain have demonstrated their efficiency against IIoT cybersecurity and privacy issues.
This Special Issue will cover a wide range of IIoT cybersecurity and privacy solutions, combining a plethora of emerging technologies. Researchers are invited to submit novel contributions in, but not limited to, the following topics:
- Cybersecurity analysis of IIoT communication protocols;
- Privacy issues and solutions in IIoT communication protocols;
- Threat modelling and vulnerability assessment in IIoT ecosystems;
- Collaborative risk assessment for IIoT ecosystems;
- SDN/NFV-based cybersecurity architectures for IIoT ecosystems;
- FL cybersecurity and privacy-preserving architectures for IIoT ecosystems;
- AI-based intrusion detection for IIoT ecosystems;
- AI-based intrusion mitigation and prevention solutions for IIoT ecosystems;
- SDN-based intrusion mitigation and prevention solutions for IIoT ecosystems;
- Security information and event management systems for IIoT ecosystems;
- Trust management in IIoT ecosystems;
- FL-based privacy-preserving architectures for detecting intrusions in IIoT ecosystems;
- Blockchain-based authentication and access control systems for IIoT ecosystems;
- Self-healing cybersecurity mechanisms in IIoT ecosystems;
- Orchestration and automatic configuration of security functions;
- Privacy-preserving tools, frameworks and schemes in IIoT ecosystems;
- Cybersecurity deception mechanisms in IIoT ecosystems;
- Cyber threat intelligence management and sharing in IIoT ecosystems;
- Digital forensics in IIoT ecosystems;
- Surveys and technical reports related to cybersecurity and privacy incidents in IIoT ecosystems.
Dr. Panagiotis Radoglou-Grammatikis
Dr. Panagiotis Sarigiannidis
Dr. Thomas Lagkas
Prof. Dr. Vasileios Argyriou
Guest Editors
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Keywords
- Artificial Intelligence
- Blockchain
- Cybersecurity
- Cyber threat intelligence
- Digital forensics
- Federated learning
- Industrial Internet of Things
- Intrusion detection and prevention
- Network function virtualization
- Privacy
- Risk assessment
- Security information and event management
- Software-defined networking
- Threat modelling
- Trust management
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