Convolutional Neural Network-Based Classification of Secured IEC 104 Traffic in Energy Systems-Reference-Cited by-同舟云学术

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Convolutional Neural Network-Based Classification of Secured IEC 104 Traffic in Energy Systems

Published:2023-12-06 Issue: Volume: Page:159-165
ISSN:
Container-title:Proceedings of the 2023 13th International Conference on Communication and Network Security
language:
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Author:

Bohacik Antonin¹^ORCID,Holasova Eva²^ORCID,Fujdiak Radek²^ORCID,Racka Jan²^ORCID

Affiliation:

1. Department of Telecommunications, Brno University of Technology, FEKT, Technicka 12, Brno 616 00, Czech Republic, Czech Republic and Department of Telecommunications, Brno University of Technology, FEKT, Technicka 12, Brno 616 00, Czech Republic, Czech Republic

2. Department of Telecommunications, Brno University of Technology, Czech Republic and Department of Telecommunications, Brno University of Technology, Czech Republic

Funder

Technology Agency of the Czech Republic

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3638782.3638806

Reference10 articles.

1. Convolutional neural network-based identification of malicious traffic for TLS encryption

2. Yong Fang, Yijia Xu, Cheng Huang, Liang Liu, and Lei Zhang. 2020. Against Malicious SSL/TLS Encryption: Identify Malicious Traffic Based on Random Forest. In Fourth International Congress on Information and Communication Technology, Xin-She Yang, Simon Sherratt, Nilanjan Dey, and Amit Joshi (Eds.). Springer Singapore, Singapore, 99–115.

3. An Anomaly Detection Mechanism for IEC 60870-5-104

4. Overview of intrusion detection and intrusion prevention

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