ArticleSensors (Basel, Switzerland)2025
Cybersecurity Solutions for Industrial Internet of Things-Edge Computing Integration: Challenges, Threats, and Future Directions.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Adversarial Machine Learning in Industrial IoT: A Systematic Review of Attack Realism, Defense Trade-Offs, and Deployment Gaps.Sensors (Basel, Switzerland) · 2026Review
- Optimization of sustainable supply chains under uncertainty: integrating Internet of Things and blockchain.Scientific reports · 2026Article
- GLANet: global and local anomaly network for distributed cyber threat detection using FL.Scientific reports · 2026Article
- DynamicFU: Contribution-Aware Dynamic Federated Unlearning for Industrial IoT.Sensors (Basel, Switzerland) · 2026Article
- Adaptive Multi-Model Hierarchical Federated Learning for Robust IoT Intrusion Detection.Sensors (Basel, Switzerland) · 2026Article
- BERT-spaCy hybrid NLP and blockchain-enhanced adaptive CTI for IOC extraction and threat prediction.Scientific reports · 2026Article
- ASTRID-Net: SE-enhanced triple attention deep learning framework for IoT and IIoT security.Scientific reports · 2026Article
- Integrating NLP and Ensemble Learning into Next-Generation Firewalls for Robust Malware Detection in Edge Computing.Sensors (Basel, Switzerland) · 2026Article
- EHFOA-ID: An Enhanced HawkFish Optimization-Driven Hybrid Ensemble for IoT Intrusion Detection.Sensors (Basel, Switzerland) · 2025Article
- AI-embedded IoT healthcare optimization with trust-aware mobile edge computing.Scientific reports · 2025Article
- The construction of an integrated cloud network digital intelligence platform for rail transit based on artificial intelligence.Scientific reports · 2025Article
- AegisGuard: A Multi-Stage Hybrid Intrusion Detection System with Optimized Feature Selection for Industrial IoT Security.Sensors (Basel, Switzerland) · 2025Article
- An Explainable Markov Chain-Machine Learning Sequential-Aware Anomaly Detection Framework for Industrial IoT Systems Based on OPC UA.Sensors (Basel, Switzerland) · 2025Article
- Composite Vulnerabilities and Hybrid Threats for Smart Sensors and Field Busses in Building Automation: A Review.Sensors (Basel, Switzerland) · 2025Review
- Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms.Scientific reports · 2025Article
- Enhancing track and field training feedback through 6G enabled transparent optical sensor networks.Scientific reports · 2025Article
- Federated Subgraph Learning via Global-Knowledge-Guided Node Generation.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper provides the complete details of current challenges and solutions in the cybersecurity of cyber-physical systems (CPS) within the context of the IIoT and its integration with edge computing (IIoT-edge computing). We systematically collected and analyzed the relevant literature from the past five years, applying a rigorous methodology to identify key sources. Our study highlights the prevalent IIoT layer attacks, common intrusion methods, and critical threats facing IIoT-edge computing environments. Additionally, we examine various types of cyberattacks targeting CPS, outlining their significant impact on industrial operations. A detailed taxonomy of primary security mechanisms for CPS within IIoT-edge computing is developed, followed by a comparative analysis of our approach against existing research. The findings underscore the widespread vulnerabilities across the IIoT architecture, particularly in relation to DoS, ransomware, malware, and MITM attacks. The review emphasizes the integration of advanced security technologies, including machine learning (ML), federated learning (FL), blockchain, blockchain-ML, deep learning (DL), encryption, cryptography, IT/OT convergence, and digital twins, as essential for enhancing the security and real-time data protection of CPS in IIoT-edge computing. Finally, the paper outlines potential future research directions aimed at advancing cybersecurity in this rapidly evolving domain.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.