48 citations · 68 across the 9 of their papers we have counts for
9 papers
Quantifiable Uncertainty: A Stochastic Consensus Multi-Agent RAG Framework for Robust Malware Detection
ElMouatez Billah Karbab
While contemporary deep learning malware detectors define a dominant defense paradigm, their sophistication also exposes them to novel structural evasion attacks, a limitation we a…
AsmRAG: LLM-Driven Malware Detection by Retrieving Functionally Similar Assembly Code
ElMouatez Billah Karbab
Deep learning malware detectors achieve high classification accuracy but suffer from severe interpretability limitations, typically returning probabilistic verdicts that lack foren…
Applying Graph Analysis for Unsupervised Fast Malware Fingerprinting
ElMouatez Billah Karbab, Mourad Debbabi
Malware proliferation is increasing at a tremendous rate, with hundreds of thousands of new samples identified daily. Manual investigation of such a vast amount of malware is an un…
Resilient and Adaptive Framework for Large Scale Android Malware Fingerprinting using Deep Learning and NLP Techniques
ElMouatez Billah Karbab, Mourad Debbabi
Android malware detection is a significat problem that affects billions of users using millions of Android applications (apps) in existing markets. This paper proposes PetaDroid, a…
Android Malware Clustering using Community Detection on Android Packages Similarity Network
ElMouatez Billah Karbab, Mourad Debbabi, Abdelouahid Derhab +1
The daily amount of Android malicious applications (apps) targeting the app repositories is increasing, and their number is overwhelming the process of fingerprinting. To address t…
Portable, Data-Driven Malware Detection using Language Processing and Machine Learning Techniques on Behavioral Analysis Reports
ElMouatez Billah Karbab, Mourad Debbabi
In response to the volume and sophistication of malicious software or malware, security investigators rely on dynamic analysis for malware detection to thwart obfuscation and packi…