Search Results for author: Samuel Schüppen

Found 2 papers, 0 papers with code

Analyzing the Real-World Applicability of DGA Classifiers

no code implementations19 Jun 2020 Arthur Drichel, Ulrike Meyer, Samuel Schüppen, Dominik Teubert

In this context, we propose one novel classifier based on residual neural networks for each of the two tasks and extensively evaluate them as well as previously proposed classifiers in a unified setting.

Making Use of NXt to Nothing: The Effect of Class Imbalances on DGA Detection Classifiers

no code implementations1 Jul 2020 Arthur Drichel, Ulrike Meyer, Samuel Schüppen, Dominik Teubert

Numerous machine learning classifiers have been proposed for binary classification of domain names as either benign or malicious, and even for multiclass classification to identify the domain generation algorithm (DGA) that generated a specific domain name.

Binary Classification Classification +1

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