Anomaly-Based Intrusion Detection in IIoT Networks Using Transformer Models

Author:

Casajús-Setién Jorge1,Bielza Concha1,Larrañaga Pedro1

Affiliation:

1. Universidad Politécnica de Madrid,Computational Intelligence Group

Funder

Spanish Ministry of Science and Innovation

Publisher

IEEE

Reference25 articles.

1. Neural machine translation by jointly learning to align and translate;bahdanau;ICLR International Conference on Learning Representations,0

2. Self-supervised and interpretable anomaly detection using network transform-ers;marino;CoRR,2022

3. Convolutional sequence to sequence learning;gehring;International Conference on Machine Learning,0

4. Self-Attention with Relative Position Representations

5. DDosTC: A Transformer-Based Network Attack Detection Hybrid Mechanism in SDN

Cited by 3 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. A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT;Computer Modeling in Engineering & Sciences;2024

2. An Intrusion Detection Method for Industrial Internet Fusing Multi-Scale TCN and Transformer Network;Lecture Notes in Computer Science;2024

3. Hybrid cyber threats detection using explainable AI in Industrial IoT;2023 International Conference on Human-Centered Cognitive Systems (HCCS);2023-12-16

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