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About A Hybrid Intrution Detection Approach Based On Deep Learning
This document presents a hybrid intrusion detection approach that uses deep learning and machine learning techniques. The approach first converts network traffic data into images and then uses convolutional neural networks (CNNs) for feature extraction. An support vector machine (SVM) algorithm is then used to identify the type of attack based on the features extracted. The approach is trained and tested on the CIC-IDS2017 dataset. Experimental results show the model can accurately detect several intrusion threats and outperforms some related work for some attack types.
Detailed Information
| Author: | ['Victor Kingbuilder'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 16 |
| Language: | English |
| Format: | |
| Price: | FREE |
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