33 citations · 125 across the 13 of their papers we have counts for
12 papers · 1 filter
False Sense of Security: Leveraging XAI to Analyze the Reasoning and True Performance of Context-less DGA Classifiers
Arthur Drichel, Ulrike Meyer
The problem of revealing botnet activity through Domain Generation Algorithm (DGA) detection seems to be solved, considering that available deep learning classifiers achieve accura…
Efficient Privacy-Preserving Approximation of the Kidney Exchange Problem
Malte Breuer, Ulrike Meyer, Susanne Wetzel
The kidney exchange problem (KEP) seeks to find possible exchanges among pairs of patients and their incompatible kidney donors while meeting specific optimization criteria such as…
Solving the Kidney Exchange Problem Using Privacy-Preserving Integer Programming (Updated and Extended Version)
Malte Breuer, Pascal Hein, Leonardo Pompe +3
The kidney exchange problem (KEP) is to find a constellation of exchanges that maximizes the number of transplants that can be carried out for a set of pairs of patients with kidne…
Detecting Unknown DGAs without Context Information
Arthur Drichel, Justus von Brandt, Ulrike Meyer
New malware emerges at a rapid pace and often incorporates Domain Generation Algorithms (DGAs) to avoid blocking the malware's connection to the command and control (C2) server. Cu…
Privacy-Preserving Maximum Matching on General Graphs and its Application to Enable Privacy-Preserving Kidney Exchange
Malte Breuer, Ulrike Meyer, Susanne Wetzel
To this day, there are still some countries where the exchange of kidneys between multiple incompatible patient-donor pairs is restricted by law. Typically, legal regulations in th…
Introducing a Framework to Enable Anonymous Secure Multi-Party Computation in Practice (Extended Version)
Malte Breuer, Ulrike Meyer, Susanne Wetzel
Secure Multi-Party Computation (SMPC) allows a set of parties to securely compute a functionality in a distributed fashion without the need for any trusted external party. Usually,…
Sharing FANCI Features: A Privacy Analysis of Feature Extraction for DGA Detection
Benedikt Holmes, Arthur Drichel, Ulrike Meyer
The goal of Domain Generation Algorithm (DGA) detection is to recognize infections with bot malware and is often done with help of Machine Learning approaches that classify non-res…
Finding Phish in a Haystack: A Pipeline for Phishing Classification on Certificate Transparency Logs
Arthur Drichel, Vincent Drury, Justus von Brandt +1
Current popular phishing prevention techniques mainly utilize reactive blocklists, which leave a ``window of opportunity'' for attackers during which victims are unprotected. One p…
First Step Towards EXPLAINable DGA Multiclass Classification
Arthur Drichel, Nils Faerber, Ulrike Meyer
Numerous malware families rely on domain generation algorithms (DGAs) to establish a connection to their command and control (C2) server. Counteracting DGAs, several machine learni…
A Privacy-Preserving Protocol for the Kidney Exchange Problem
Malte Breuer, Ulrike Meyer, Susanne Wetzel +1
Kidney donations from living donors form an attractive alternative to long waiting times on a list for a post-mortem donation. However, even if a living donor for a given patient i…
Making Use of NXt to Nothing: The Effect of Class Imbalances on DGA Detection Classifiers
Arthur Drichel, Ulrike Meyer, Samuel Schüppen +1
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…
Analyzing the Real-World Applicability of DGA Classifiers
Arthur Drichel, Ulrike Meyer, Samuel Schüppen +1
Separating benign domains from domains generated by DGAs with the help of a binary classifier is a well-studied problem for which promising performance results have been published.…