Smart Meter Modbus RS-485 Intrusion Detection by Federated Learning Approach-Reference-Cited by-同舟云学术

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Smart Meter Modbus RS-485 Intrusion Detection by Federated Learning Approach

Published:2023-03-03 Issue: Volume: Page:
ISSN:
Container-title:2023 15th International Conference on Computer and Automation Engineering (ICCAE)
language:
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Author:

Hossain Md Delwar¹,Ochiai Hideya²,Khan Latifur³,Kadobayashi Youki¹

Affiliation:

1. Nara Institute of Science and Technology,Division of Information Science,Ikoma,Nara,Japan

2. The University of Tokyo,Grad. School of Info. Science and Tech.,Tokyo,Japan

3. The University of Texas at Dallas,Department of Computer Science,Dallas,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10111091/10111098/10111132.pdf?arnumber=10111132

Reference13 articles.

1. Smart Meter Modbus RS-485 Spoofing Attack Detection by LSTM Deep Learning Approach

2. Unsupervised Anomaly Detection in RS-485 Traffic using Autoencoders with Unobtrusive Measurement

3. Data-Stream-Based Intrusion Detection System for Advanced Metering Infrastructure in Smart Grid: A Feasibility Study

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1. Design of Robust Hospital Nursing Call Communication System Considering Anti-Collision Algorithm;2024 International Conference on Expert Clouds and Applications (ICOECA);2024-04-18

2. A fog-edge-enabled intrusion detection system for smart grids;Journal of Cloud Computing;2024-02-14

3. Modbus Extension Server Implementation for BIoT-Enabled Smart Switch Embedded System Device;Sensors;2024-01-12

4. End-Edge Collaborative Lightweight Secure Federated Learning for Anomaly Detection of Wireless Industrial Control Systems;IEEE Open Journal of the Industrial Electronics Society;2024

5. BDVFL: Blockchain-based Decentralized Vertical Federated Learning;2023 IEEE International Conference on Data Mining (ICDM);2023-12-01

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