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About ML Paper 2
This document compares different deep learning architectures for character-level classification of domain names as either benign or generated by malware. It finds that convolutional neural networks (CNNs) and recurrent neural networks (RNNs) perform similarly for this task, with little difference in accuracy. This suggests simpler architectures are preferable since they are faster to train and less prone to overfitting. The paper evaluates five deep learning models on a dataset of over 2 million domain names, finding they all outperform traditional machine learning methods for this cybersecurity problem of detecting domain generation algorithms (DGAs) used by malware.
Detailed Information
| Author: | ['lydia'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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