activity
20202024
most citedAnalyzing the Real-World Applicability of DGA Classifiers

33 citations · 148 across the 11 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.CR2021★ 27 cited

CoinPrune: Shrinking Bitcoin's Blockchain Retrospectively

Roman Matzutt, Benedikt Kalde, Jan Pennekamp +3

Popular cryptocurrencies continue to face serious scalability issues due to their ever-growing blockchains. Thus, modern blockchain designs began to prune old blocks and rely on re…

cs.CR2021

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…

cs.CR2021★ 9 cited

The More, the Better? A Study on Collaborative Machine Learning for DGA Detection

Arthur Drichel, Benedikt Holmes, Justus von Brandt +1

Domain generation algorithms (DGAs) prevent the connection between a botnet and its master from being blocked by generating a large number of domain names. Promising single-data-so…

cs.CR2021★ 24 cited

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…

cs.CR2021★ 18 cited

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…