End-Edge Collaborative Lightweight Secure Federated Learning for Anomaly Detection of Wireless Industrial Control Systems

End-Edge Collaborative Lightweight Secure Federated Learning for Anomaly Detection of Wireless Industrial Control Systems

With the wide applications of industrial wireless network technologies, the industrial control system (ICS) is evolving from wired and centralized to wireless and distributed, during which eavesdropping and attacking become serious problems. To guarantee the security of wireless and distributed ICS,...

Full description

Bibliographic Details
Main Authors:	Chi Xu, Xinyi Du, Lin Li, Xinchun Li, Haibin Yu
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Series:	IEEE Open Journal of the Industrial Electronics Society
Subjects:	Industrial control system (ICS) anomaly detection federated learning convolutional neural network (CNN)
Online Access:	https://ieeexplore.ieee.org/document/10449459/

Similar Items

Federated Learning-Based Explainable Anomaly Detection for Industrial Control Systems
by: Truong Thu Huong, et al.
Published: (2022-01-01)

Design of an improved graph-based model for real-time anomaly detection in healthcare using hybrid CNN-LSTM and federated learning
by: G Muni Nagamani, et al.
Published: (2024-12-01)

Enhanced federated anomaly detection through autoencoders using summary statistics-based thresholding
by: Sofiane Laridi, et al.
Published: (2024-11-01)

An On-Device Federated Learning Approach for Cooperative Model Update Between Edge Devices
by: Rei Ito, et al.
Published: (2021-01-01)

An improved autoencoder-based approach for anomaly detection in industrial control systems
by: Muhammad Muzamil Aslam, et al.
Published: (2024-12-01)

Asynchronous Real-Time Federated Learning for Anomaly Detection in Microservice Cloud Applications
by: Mahsa Raeiszadeh, et al.
Published: (2025-01-01)

Utility Analysis about Log Data Anomaly Detection Based on Federated Learning
by: Tae-Ho Shin, et al.
Published: (2023-04-01)

Chained Anomaly Detection Models for Federated Learning: An Intrusion Detection Case Study
by: Davy Preuveneers, et al.
Published: (2018-12-01)

Enhancing IoT anomaly detection performance for federated learning
by: Brett Weinger, et al.
Published: (2022-06-01)

Anomaly Detection Method for Unknown Protocols in a Power Plant ICS Network with Decision Tree
by: Kyoung-Mun Lee, et al.
Published: (2023-03-01)

FedADMP: A Joint Anomaly Detection and Mobility Prediction Framework via Federated Learning
by: Zezhang Yang, et al.
Published: (2021-11-01)

FedPSO: Federated Learning Using Particle Swarm Optimization to Reduce Communication Costs
by: Sunghwan Park, et al.
Published: (2021-01-01)

Decentralized Federated Learning-Enabled Relation Aggregation for Anomaly Detection
by: Siyue Shuai, et al.
Published: (2023-12-01)

Multigranularity Feature Automatic Marking-Based Deep Learning for Anomaly Detection of Industrial Control Systems
by: Xinyi Du, et al.
Published: (2024-01-01)

Intelligent depression detection with asynchronous federated optimization
by: Jinli Li, et al.
Published: (2022-06-01)

Deep anomaly detection through visual attention in surveillance videos
by: Nasaruddin Nasaruddin, et al.
Published: (2020-10-01)

Edge Detection of Source Body from Magnetic Anomaly Based on ResNet
by: Xinyi Zhou, et al.
Published: (2024-11-01)

Unified ensemble federated learning with cloud computing for online anomaly detection in energy-efficient wireless sensor networks
by: S. Gayathri, et al.
Published: (2024-02-01)

Cloud–Edge–End Collaborative Federated Learning: Enhancing Model Accuracy and Privacy in Non-IID Environments
by: Ling Li, et al.
Published: (2024-12-01)

Adaptive Resource Optimized Edge Federated Learning in Real-Time Image Sensing Classifications
by: Prohim Tam, et al.
Published: (2021-01-01)

Decentralized Federated Learning on the Edge Over Wireless Mesh Networks
by: Abdelaziz Salama, et al.
Published: (2023-01-01)

EdgeFed: Optimized Federated Learning Based on Edge Computing
by: Yunfan Ye, et al.
Published: (2020-01-01)

Enhancing diabetic retinopathy detection through federated convolutional neural networks: Exploring different stages of progression
by: Saad Alanazi, et al.
Published: (2025-05-01)

DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
by: Chuanqi Lao, et al.
Published: (2024-03-01)

A Federated Learning Approach for Efficient Anomaly Detection in Electric Power Steering Systems
by: Kimleang Kea, et al.
Published: (2024-01-01)

Feature-Attended Federated LSTM for Anomaly Detection in the Financial Internet of Things
by: Yunlong Li, et al.
Published: (2024-06-01)

Fetal Organ Anomaly Classification Network for Identifying Organ Anomalies in Fetal MRI
by: Justin Lo, et al.
Published: (2022-03-01)

Federated Learning for Predictive Maintenance and Anomaly Detection Using Time Series Data Distribution Shifts in Manufacturing Processes
by: Jisu Ahn, et al.
Published: (2023-08-01)

Distributed Anomaly Detection in Smart Grids: A Federated Learning-Based Approach
by: J. Jithish, et al.
Published: (2023-01-01)

Anomaly detection in log-event sequences: A federated deep learning approach and open challenges
by: Patrick Himler, et al.
Published: (2024-06-01)

Deep anomaly detection for time-series data in industrial IoT: a communication-efficient on-device federated learning approach
by: Liu, Yi, et al.
Published: (2022)

Adaptive Dataset Management Scheme for Lightweight Federated Learning in Mobile Edge Computing
by: Jingyeom Kim, et al.
Published: (2024-04-01)

Time Series Anomaly Detection for KPIs Based on Correlation Analysis and HMM
by: Zijing Shang, et al.
Published: (2021-11-01)

Hyperspectral Image Super Resolution Using Anomaly Weighted Gabor Based CNN
by: Ali Farajzadeh, et al.
Published: (2023-03-01)

Tucker Decomposition-Based Network Compression for Anomaly Detection With Large-Scale Hyperspectral Images
by: Yulei Wang, et al.
Published: (2024-01-01)

E-SFD: Explainable Sensor Fault Detection in the ICS Anomaly Detection System
by: Chanwoong Hwang, et al.
Published: (2021-01-01)

Visibility Graph-Based Wireless Anomaly Detection for Digital Twin Edge Networks
by: Blaz Bertalanic, et al.
Published: (2024-01-01)

A lightweight and personalized edge federated learning model
by: Peiyan Yuan, et al.
Published: (2024-02-01)

Enhancing Robustness within the Collaborative Federated Learning Framework: A Novel Grouping Algorithm for Edge Clients
by: Zhi-Yuan Su, et al.
Published: (2024-04-01)

Improving Graph Convolutional Network with Learnable Edge Weights and Edge-Node Co-Embedding for Graph Anomaly Detection
by: Xiao Tan, et al.
Published: (2024-04-01)