1 citations · 1 across the 6 of their papers we have counts for
7 papers
On the use of LLMs to generate a dataset of Neural Networks
Nadia Daoudi, Jordi Cabot
Neural networks are increasingly used to support decision-making. To verify their reliability and adaptability, researchers and practitioners have proposed a variety of tools and m…
Towards Migrating Neural Network Implementations
Nadia Daoudi, Ivan Alfonso, Jordi Cabot
The development of smart systems (i.e., systems enhanced with AI components) has thrived thanks to the rapid advancements in neural networks (NNs). A wide range of libraries and fr…
DetectBERT: Towards Full App-Level Representation Learning to Detect Android Malware
Tiezhu Sun, Nadia Daoudi, Kisub Kim +3
Recent advancements in ML and DL have significantly improved Android malware detection, yet many methodologies still rely on basic static analysis, bytecode, or function call graph…
LaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learning
Tiezhu Sun, Weiguo Pian, Nadia Daoudi +3
Transfomer-based models have significantly advanced natural language processing, in particular the performance in text classification tasks. Nevertheless, these models face challen…
A two-steps approach to improve the performance of Android malware detectors
Nadia Daoudi, Kevin Allix, Tegawendé F. Bissyandé +1
The popularity of Android OS has made it an appealing target to malware developers. To evade detection, including by ML-based techniques, attackers invest in creating malware that…
JuCify: A Step Towards Android Code Unification for Enhanced Static Analysis
Jordan Samhi, Jun Gao, Nadia Daoudi +6
Native code is now commonplace within Android app packages where it co-exists and interacts with Dex bytecode through the Java Native Interface to deliver rich app functionalities.…
DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection based on Image Representation of Bytecode
Nadia Daoudi, Jordan Samhi, Abdoul Kader Kabore +3
Computer vision has witnessed several advances in recent years, with unprecedented performance provided by deep representation learning research. Image formats thus appear attracti…