11 citations · 12 across the 8 of their papers we have counts for
9 papers
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…
DexBERT: Effective, Task-Agnostic and Fine-grained Representation Learning of Android Bytecode
Tiezhu Sun, Kevin Allix, Kisub Kim +5
The automation of a large number of software engineering tasks is becoming possible thanks to Machine Learning (ML). Central to applying ML to software artifacts (like source or ex…
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…
A First Look at Android Applications in Google Play related to Covid-19
Jordan Samhi, Kevin Allix, Tegawendé F. Bissyandé +1
Due to the convenience of access-on-demand to information and business solutions, mobile apps have become an important asset in the digital world. In the context of the Covid-19 pa…
Learning to Catch Security Patches
Arthur D. Sawadogo, Tegawendé F. Bissyandé, Naouel Moha +4
Timely patching is paramount to safeguard users and maintainers against dire consequences of malicious attacks. In practice, patching is prioritized following the nature of the cod…
In-Vivo Bytecode Instrumentation for Improving Privacy on Android Smartphones in Uncertain Environments
Alexandre Bartel, Jacques Klein, Martin Monperrus +2
In this paper we claim that an efficient and readily applicable means to improve privacy of Android applications is: 1) to perform runtime monitoring by instrumenting the applicati…