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Privacy-Preserving Federated Learning-Based Intrusion Detection Technique for Cyber-Physical Systems

https://doi.org/10.3390/math12203194

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Cyber Threat Intelligence Sharing Scheme Based on Federated Learning for Network Intrusion Detection

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Federated Learning for Healthcare Informatics

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Security Considerations for Internet of Things: A Survey

inferredcites →https://doi.org/10.1007/s44244-023-00006-2openalex-snapshot

FSL: federated sequential learning-based cyberattack detection for Industrial Internet of Things

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On the security of SSL/TLS-enabled applications

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FLAD: Adaptive Federated Learning for DDoS attack detection

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Deep learning to filter SMS Spam

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Transfer learning based intrusion detection scheme for Internet of vehicles

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Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications

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TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems

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Distributed Network Intrusion Detection System in Satellite-Terrestrial Integrated Networks Using Federated Learning

inferredcites →https://doi.org/10.1109/access.2020.3041793openalex-snapshot

Intrusion Detection for Wireless Edge Networks Based on Federated Learning

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Federated Learning-Based Explainable Anomaly Detection for Industrial Control Systems

inferredcites →https://doi.org/10.1109/comst.2018.2854724openalex-snapshot

From Intrusion Detection to Attacker Attribution: A Comprehensive Survey of Unsupervised Methods

inferredcites →https://doi.org/10.1109/comst.2020.2986024openalex-snapshot

Federated Learning in Mobile Edge Networks: A Comprehensive Survey

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Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges

inferredcites →https://doi.org/10.1109/jiot.2021.3100755openalex-snapshot

Federated Deep Learning for Zero-Day Botnet Attack Detection in IoT-Edge Devices

inferredcites →https://doi.org/10.1109/mce.2019.2959108openalex-snapshot

Preserving Data Privacy via Federated Learning: Challenges and Solutions

inferredcites →https://doi.org/10.1109/ojcs.2020.2993259openalex-snapshot

Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge Based Framework

inferredcites →https://doi.org/10.1109/tii.2014.2300753openalex-snapshot

Internet of Things in Industries: A Survey

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Industrial Internet of Things: Challenges, Opportunities, and Directions

inferredcites →https://doi.org/10.1109/tii.2020.3023430openalex-snapshot

DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems

inferredcites →https://doi.org/10.1109/tii.2021.3126728openalex-snapshot

Intrusion Detection Based on Privacy-Preserving Federated Learning for the Industrial IoT

inferredcites →https://doi.org/10.1109/tii.2022.3164770openalex-snapshot

Dependable Intrusion Detection System for IoT: A Deep Transfer Learning Based Approach

inferredcites →https://doi.org/10.1145/3271432openalex-snapshot

Dependability in Cyber-Physical Systems and Applications

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A Systematic Literature Review on Federated Machine Learning

inferredcites →https://doi.org/10.1145/3485730.3493444openalex-snapshot

Federated Learning for Internet of Things

inferredcites →https://doi.org/10.1155/2021/6610675openalex-snapshot

A Novel Framework Design of Network Intrusion Detection Based on Machine Learning Techniques

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ViraMiner: Deep learning on raw DNA sequences for identifying viral genomes in human samples

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Federated learning for intrusion detection in IoT security: a hybrid ensemble approach

inferredcites →https://doi.org/10.32604/csse.2023.027216openalex-snapshot

Intrusion Detection Using Federated Learning for Computing

inferredcites →https://doi.org/10.32604/iasc.2022.023763openalex-snapshot

Federated Learning for Privacy-Preserved Medical Internet of Things

inferredcites →https://doi.org/10.3390/ai4030028openalex-snapshot

Federated Learning for IoT Intrusion Detection

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Reviewing Federated Learning Aggregation Algorithms; Strategies, Contributions, Limitations and Future Perspectives

inferredcites →https://doi.org/10.3390/fi13040094openalex-snapshot

Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning

What points at this work

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Recurrent Neural Network with Chaotic Henry Gas Solubility Optimization Algorithm for Predicting Privacy Preservation in Edge Computing

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Federated learning-based misbehavior classification system for VANET intrusion detection

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Ensemble probability meta-classifier for attack detection leveraging user behavior and big data analytics

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Hybrid dynamic feature convolution with transformer fusion model for the detection of intrusion during manufacturing process

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Federated learning for sustainable intrusion detection systems: A review of green computing strategies and future directions

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Adversarial attacks against network intrusion detection systems: Bridging the gap between theoretical vulnerabilities and practical constraints

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inferred← citeshttps://doi.org/10.1016/j.procs.2026.06.553openalex-snapshot

User-Interactive Federated Learning for Automated Endpoint Intrusion Detection with Real-Time Visualization and Incremental Threat Adaptation

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inferred← citeshttps://doi.org/10.1109/balkancom71095.2026.11605017openalex-snapshot

FedVAE-KD: A Privacy-Preserving Federated Learning Framework for Scalable Wireless Network Intrusion Detection

inferred← citeshttps://doi.org/10.1109/evst69093.2026.11660530openalex-snapshot

Secure Federated Learning Framework for Privacy-Preserving Intrusion Detection under Adversarial Attacks

inferred← citeshttps://doi.org/10.1109/fuzz69877.2026.11626376openalex-snapshot

Empirical Bernstein Certified Bandit-KL Mixing with Tree Stacking for Explainable Federated Intrusion Detection

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Adaptive Deep Learning-Based Intrusion Detection and Prevention System for Encrypted Network Traffic

inferred← citeshttps://doi.org/10.1109/iccrtee68719.2026.11566161openalex-snapshot

Secure and Privacy-Preserving Fine-Tuning of Large Language Models via Homomorphic Gradient Aggregation

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Q-Mask: Quantized Masking for Practical Secure Aggregation in Federated Intrusion Detection on IoT

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Quantum-Resilient Federated Learning for Secure and Scalable Cyber-Physical Systems

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FedShield: Privacy-Preserving Federated Deep Learning for IoT Intrusion Detection

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Emerging Technologies in Cybersecurity: Key Concepts and Future Impact

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SecureDyn-FL: A Robust Privacy-Preserving Federated Learning Framework for Intrusion Detection in IoT Networks

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Fortifying the Cloud: AI-Driven Federated Learning for Intrusion Detection and Cyber Resilience

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Feature resonance classifier: a novel neural network for efficient network traffic classification

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FL-P4AV: A Federated Learning-Based Privacy-Preserving Personalized Path Planning Framework for Collaborative Autonomous Ground Vehicles

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Privacy Preserving Model for Efficient Designing of Intrusion Detection Systems in IoT Environment

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Intelligent defense at the edge: a comprehensive survey of federated learning, TinyML and explainable AI for intrusion detection in IoT and IIoT ecosystems

inferred← citeshttps://doi.org/10.3390/electronics15030494openalex-snapshot

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