Neural Networks Optimizations Against Concept and Data Drift in Malware Detection

no code implementations • 21 Aug 2023 • William Maillet, Benjamin Marais

Despite the promising results of machine learning models in malware detection, they face the problem of concept drift due to malware constant evolution.

Malware Detection

AI-based Malware and Ransomware Detection Models

no code implementations • 5 Jul 2022 • Benjamin Marais, Tony Quertier, Stéphane Morucci

Cybercrime is one of the major digital threats of this century.

Malware Detection

MERLIN -- Malware Evasion with Reinforcement LearnINg

no code implementations • 24 Mar 2022 • Tony Quertier, Benjamin Marais, Stéphane Morucci, Bertrand Fournel

In this paper, we propose a method using reinforcement learning with DQN and REINFORCE algorithms to challenge two state-of-the-art ML-based detection engines (MalConv \& EMBER) and a commercial AV classified by Gartner as a leader AV.

Malware Detection reinforcement-learning +1

Malware Analysis with Artificial Intelligence and a Particular Attention on Results Interpretability

no code implementations • 23 Jul 2021 • Benjamin Marais, Tony Quertier, Christophe Chesneau

Therefore, we propose a model based on the transformation of binary files into grayscale image, which achieves an accuracy rate of 88%.

Malware Analysis Malware Detection