Mitigating IEC-60870-5-104 Vulnerabilities: Anomaly Detection in Smart Grid based on LSTM Autoencoder
Author:
Affiliation:
1. College of Science and Engineering, Hamad Bin Khalifa University,Division of Information and Computing Technology,Doha,Qatar
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10323591/10323546/10323610.pdf?arnumber=10323610
Reference35 articles.
1. A comprehensive survey on design and application of autoencoder in deep learning
2. Anomaly Detection for Simulated IEC-60870-5-104 Trafiic
3. A Survey On Network Packet Inspection And ARP Poisoning Using Wireshark And Ettercap
4. An Anomaly Detection Mechanism for IEC 60870-5-104
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey;IEEE Internet of Things Journal;2024-05-01
2. Double-Edged Defense: Thwarting Cyber Attacks and Adversarial Machine Learning in IEC 60870-5-104 Smart Grids;IEEE Open Journal of the Industrial Electronics Society;2023
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