2 citations · 3 across the 4 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2021★ 1 cited
Improving Robustness of Malware Classifiers using Adversarial Strings Generated from Perturbed Latent Representations
Marek Galovic, Branislav Bosansky, Viliam Lisy
In malware behavioral analysis, the list of accessed and created files very often indicates whether the examined file is malicious or benign. However, malware authors are trying to…
cs.LG2020
Discovering Imperfectly Observable Adversarial Actions using Anomaly Detection
Olga Petrova, Karel Durkota, Galina Alperovich +4
Anomaly detection is a method for discovering unusual and suspicious behavior. In many real-world scenarios, the examined events can be directly linked to the actions of an adversa…