most citedImproving DGA-Based Malicious Domain Classifiers for Malware Defense with Adversarial Machine Learning

1 citations · 1 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CR2021★ 1 cited

Improving DGA-Based Malicious Domain Classifiers for Malware Defense with Adversarial Machine Learning

Ibrahim Yilmaz, Ambareen Siraj, Denis Ulybyshev

Domain Generation Algorithms (DGAs) are used by adversaries to establish Command and Control (C\&C) server communications during cyber attacks. Blacklists of known/identified C\&C…