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About (1-0) A Transfer Learning Approach For Network Intrusion Detection
This document proposes a transfer learning approach using convolutional neural networks for network intrusion detection. It introduces a two-stage training process where a base model first learns from an existing dataset and then transfers that knowledge to learn a target dataset. Experiments on the NSL-KDD dataset show this approach improves detection accuracy for known and unknown attacks compared to traditional convolutional neural networks.
Detailed Information
| Author: | ['Bach Nguyen'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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