New Open-Access Dataset Released for Adversarial Malware Research
The project team has published WinAPI-AdvMal, an open-access dataset for adversarial malware generation and detection evasion experiments.
Project Results Recognized at International AI Conference in Tokyo
Project findings were presented at the International Conference on Advances in Artificial Intelligence and Machine Learning (AAIML)
Participation in 16th Conference „Data Analysis Methods for Software Systems”
The project team will present several research papers focusing on advanced applications of ethical adversarial machine learning for cybersecurity.
Project results presented at the 23rd IEEE International Symposium
The ongoing results of the project were presented at the 23rd IEEE International Symposium on Network Computing and Applications at Instituto Superior Técnico.
A new publicly available dataset WinAPI-4C-AdvMal published in MIDAS.
We introduce WinAPI-4C-AdvMal, a public Windows API malware dataset enabling research on adversarial attacks, obfuscation, and robust detection methods techniques.
Notes from DeepLearn 2025, Porto — a week on the frontier of deep neural networks
One of our researchers spent the last week of July at DeepLearn 2025 in Porto, Portugal, hosted at Universidade da
Improving Malware Detection via Multi-Class Benign Software Analysis
We’ve published a short paper (in Lithuanian) presented at “Lietuvos magistrantų informatikos ir IT tyrimai” on May 13, 2025 and
Red Team Tactics Against Malware Detection Using Adversarial Attacks
We’re happy to share our short paper presented at DAMSS 2024 (Druskininkai, Lithuania, Nov 28–30, 2024) and published in Vilnius