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About A Machine Learning Framework For Domain Generation Algorithm (DGA) - Based Malware Detection
This article proposes a machine learning framework to detect domains generated by domain generation algorithms (DGAs) used by malware. The framework consists of a two-level classification model to distinguish DGA and normal domains, and identify the specific DGA algorithm. It also includes a Hidden Markov Model to predict incoming domain features over time based on historical data. Evaluation of the framework achieved 95.89% accuracy for classifying domains, 92.45% for clustering DGA algorithms, and 95.21% for predictive modeling. A deep neural network model is also proposed to handle the large dataset collected over one year for enhanced analysis.
Detailed Information
Author: | ['Guddi Shelar'] |
---|---|
Publication Year: | 2021 |
Pages: | 18 |
Language: | English |
Format: | |
Price: | FREE |
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