Fed-IIoT: A Robust Federated Malware Detection Architecture in Industrial IoT

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A Privacy-Aware and Incremental Defense Method Against GAN-Based Poisoning Attack

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Blockchain and federated learning-based intrusion detection approaches for edge-enabled industrial IoT networks: a survey

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Federated Semisupervised Learning for Attack Detection in Industrial Internet of Things

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Drones’ Edge Intelligence Over Smart Environments in B5G: Blockchain and Federated Learning Synergy

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2DF-IDS: Decentralized and differentially private federated learning-based intrusion detection system for industrial IoT

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Privacy-Preserving Federated Learning for Industrial Edge Computing via Hybrid Differential Privacy and Adaptive Compression

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Edge Intelligence for Data Handling and Predictive Maintenance in IIOT

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Blockchain-Based Two-Stage Federated Learning With Non-IID Data in IoMT System

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A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things

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SecFedNIDS: Robust defense for poisoning attack against federated learning-based network intrusion detection system

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Key Challenges and Emerging Technologies in Industrial IoT Architectures: A Review

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SCA: Sybil-Based Collusion Attacks of IIoT Data Poisoning in Federated Learning

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Class-Incremental Learning for Wireless Device Identification in IoT

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Federated Learning for IoMT Applications: A Standardization and Benchmarking Framework of Intrusion Detection Systems

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Federated learning for 6G-enabled secure communication systems: a comprehensive survey

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Byzantine-Robust Aggregation in Federated Learning Empowered Industrial IoT

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Data-Driven Detection of Stealthy False Data Injection Attack Against Power System State Estimation

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A Systematic Literature Review of Robust Federated Learning: Issues, Solutions, and Future Research Directions

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Forward Privacy Preservation in IoT-Enabled Healthcare Systems

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Cybersecurity threats in FinTech: A systematic review

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A Survey of Industrial AIoT: Opportunities, Challenges, and Directions

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Ranking Security of IoT-Based Smart Home Consumer Devices

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Machine Learning-Based Security Solutions for IoT Networks: A Comprehensive Survey

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Adversarial Attacks and Defenses in 6G Network-Assisted IoT Systems

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DisBezant: Secure and Robust Federated Learning Against Byzantine Attack in IoT-Enabled MTS

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Efficient intrusion detection toward IoT networks using cloud–edge collaboration

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Privacy-Preserved Generative Network for Trustworthy Anomaly Detection in Smart Grids: A Federated Semisupervised Approach

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Comprehensive Android Malware Detection Based on Federated Learning Architecture

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Attention-Based Multidimensional Deep Learning Approach for Cross-Architecture IoMT Malware Detection and Classification in Healthcare Cyber-Physical Systems

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Intrusion Detection Based on Federated Learning: A Systematic Review

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C-FDRL: Context-Aware Privacy-Preserving Offloading Through Federated Deep Reinforcement Learning in Cloud-Enabled IoT

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Privacy-Preserved Cyberattack Detection in Industrial Edge of Things (IEoT): A Blockchain-Orchestrated Federated Learning Approach

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Asynchronous Peer-to-Peer Federated Capability-Based Targeted Ransomware Detection Model for Industrial IoT

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Insights into Modern Intrusion Detection Strategies for Internet of Things Ecosystems

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Federated Learning for Enhanced Cybersecurity and Trustworthiness in 5G and 6G Networks: A Comprehensive Survey

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Federated-Learning-Empowered Semi-Supervised Active Learning Framework for Intrusion Detection in ZSM

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Machine Learning for Android Malware Detection: Mission Accomplished? A Comprehensive Review of Open Challenges and Future Perspectives

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BC-EdgeFL: A Defensive Transmission Model Based on Blockchain-Assisted Reinforced Federated Learning in IIoT Environment

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Efficient and Lightweight Convolutional Networks for IoT Malware Detection: A Federated Learning Approach

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Particle Swarm-Based Federated Learning Approach for Early Detection of Forest Fires

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Federated learning at the edge in Industrial Internet of Things: A review

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Techniques and countermeasures for preventing insider threats

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Genetic Clustered Federated Learning for COVID-19 Detection

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A Deep Learning Method for Lightweight and Cross-Device IoT Botnet Detection

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Unveiling vulnerabilities in deep learning-based malware detection: Differential privacy driven adversarial attacks

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FedHGCDroid: An Adaptive Multi-Dimensional Federated Learning for Privacy-Preserving Android Malware Classification

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A systematic literature review for APT detection and Effective Cyber Situational Awareness (ECSA) conceptual model

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SIM-FED: Secure IoT malware detection model with federated learning

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Exploration of Mobile Device Behavior for Mitigating Advanced Persistent Threats (APT): A Systematic Literature Review and Conceptual Framework

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PCNNCEC: Efficient and Privacy-Preserving Convolutional Neural Network Inference Based on Cloud-Edge-Client Collaboration

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Threats and Defenses in the Federated Learning Life Cycle: A Comprehensive Survey and Challenges

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A Survey on Privacy and Security in Distributed Cloud Computing: Exploring Federated Learning and Beyond

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An analysis of Intrusion detection systems in IIoT

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Automated federated learning for intrusion detection of industrial control systems based on evolutionary neural architecture search

Shao, J., Zeng, G., Lu, K., Geng, G., & Weng, J. (2024) · Computers & Security · doi:10.1016/j.cose.2024.103910 · Cited by 33

DISFIDA: Distributed Self-Supervised Federated Intrusion Detection Algorithm with online learning for health Internet of Things and Internet of Vehicles

Erol Gelenbe, A., Gül, B. C., & Nakıp, M. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101340 · Cited by 33

Privacy-Preserving Baseline Load Reconstruction for Residential Demand Response Considering Distributed Energy Resources

Chen, Y., Chen, C., Zhang, X., Cui, M., Li, F. F., Wang, X., & Yin, S. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3107400 · Cited by 32

FEDetect: A Federated Learning-Based Malware Detection and Classification Using Deep Neural Network Algorithms

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Intrusion Detection Systems for Industrial Internet of Things: A Survey

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Studying the Robustness of Anti-Adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors

Sánchez, P. M. S., Celdrán, A. H., Schenk, T., Iten, A. L. B., Bovet, G., Pérez, G. M., & Stiller, B. (2022) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2022.3204535 · Cited by 33

A Blockchain-Reinforced Federated Intrusion Detection Architecture for IIoT

Jiang, D., Wang, Z., Wang, Y., Tan, L., Wang, J., & Zhang, P. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3406602 · Cited by 28

Boosting Accuracy of Differentially Private Federated Learning in Industrial IoT With Sparse Responses

Cui, L., Ma, J., Zhou, Y., & Yu, S. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3161517 · Cited by 28

Modeling and Analysis of Malware Propagation for IoT Heterogeneous Devices

Zhu, X., Huang, J., & Qi, C. (2023) · IEEE Systems Journal · doi:10.1109/jsyst.2023.3269158 · Cited by 28

Privacy-Preserving Federated Learning-Based Intrusion Detection System for IoHT Devices

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A classification-based sensor data processing method for the internet of things assimilated wearable sensor technology

Pradhan, M. R., Mago, B., & Ateeq, K. (2022) · Cluster Computing · doi:10.1007/s10586-022-03605-3 · Cited by 27

A novel anomaly detection method for multimodal WSN data flow via a dynamic graph neural network

Zhang, Q., Ye, M., & Deng, X. (2022) · Connection Science · doi:10.1080/09540091.2022.2078281 · Cited by 26

A Systematic Literature Review and a Conceptual Framework Proposition for Advanced Persistent Threats (APT) Detection for Mobile Devices Using Artificial Intelligence Techniques

Al-Kadhimi, A. A., Singh, M. M., & Khalid, M. N. A. (2023) · Applied Sciences · doi:10.3390/app13148056 · Cited by 30

FedDICE: A Ransomware Spread Detection in a Distributed Integrated Clinical Environment Using Federated Learning and SDN Based Mitigation

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A Dynamic Weighted Federated Learning for Android Malware Classification

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Distributed IIoT anomaly detection scheme based on blockchain and federated learning

Jin, X., Ma, C., Luo, S., Zeng, P., & Wei, Y. (2024) · Journal of Communications and Networks · doi:10.23919/jcn.2024.000016 · Cited by 23

Privacy-Preserving and Syscall-Based Intrusion Detection System for IoT Spectrum Sensors Affected by Data Falsification Attacks

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Generative Adversarial Networks in Cybersecurity: Analysis and Response

Striuk, O., & Kondratenko, Y. P. (2023) · Studies in computational intelligence · doi:10.1007/978-3-031-25759-9_18 · Cited by 24

Generative Adversarial Networks: A Survey Towards Private and Secure ApplicationsPreprint

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Federated learning-based robust android malware detection: label-flipping attacks and defenses

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ABM-SpConv-SIMD: Accelerating Convolutional Neural Network Inference for Industrial IoT Applications on Edge Devices

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SETTI: A S elf-supervised Adv E rsarial Malware De T ection Archi T ecture in an I oT Environment

Golmaryami, M., Taheri, R., Pooranian, Z., Shojafar, M., & Xiao, P. (2022) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3536425 · Cited by 24

Robust Aggregation Function in Federated Learning

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Zero-Bias Deep-Learning-Enabled Quickest Abnormal Event Detection in IoT

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Building Trusted Federated Learning: Key Technologies and Challenges

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Rough Fermatean fuzzy decision-based approach for modelling IDS classifiers in the federated learning of IoMT applications

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Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection

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Securing the internet of robotic things: a comprehensive review on machine learning-based intrusion detection

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Advancing Federated Learning: A Systematic Literature Review of Methods, Challenges, and Applications

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Stacking-based ensemble model for malware detection in android devices

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