A Temporal Convolutional Network-based Approach for Network Intrusion Detection
Published in 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS), 2024
Abstract: Network intrusion detection is critical for securing modern networks. This study proposes a Temporal Convolutional Network (TCN) model featuring a residual block architecture with dilated convolutions. Evaluated on the Edge-IIoTset dataset, the proposed model achieved an accuracy of 96.72% and a loss of 0.0688, outperforming ID CNN, CNN-LSTM, and CNN-BiLSTM models.
Proposed TCN Architecture: 
Recommended citation: R. Nazre, R. Budke, O. Oak, S. Sawant, A. Joshi. (2024). "A Temporal Convolutional Network-based Approach for Network Intrusion Detection." IEEE ICIICS 2024.
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