5 papers
TaintRadar: Semantic-Aware Taint-Style Vulnerability Detection via Augmented Code Property Graphs
Elie Rizk, Firas Ben Hmida, Birhanu Eshete
Despite significant advances, static vulnerability analysis suffers from three critical limitations: coarse sanitization modeling, which treats validation as a binary barrier; data…
NeuroTrace: Inference Provenance-Based Detection of Adversarial Examples
Firas Ben Hmida, Philemon Hailemariam, Kashif Ali Khan +1
Deep neural networks (DNNs) remain largely opaque at inference time, limiting our ability to detect and diagnose malicious input manipulations such as adversarial examples. Existin…
Pro-ZD: A Transferable Graph Neural Network Approach for Proactive Zero-Day Threats Mitigation
Nardine Basta, Firas Ben Hmida, Houssem Jmal +3
In today's enterprise network landscape, the combination of perimeter and distributed firewall rules governs connectivity. To address challenges arising from increased traffic and…
DeepLeak: Privacy Enhancing Hardening of Model Explanations Against Membership Leakage
Firas Ben Hmida, Zain Sbeih, Philemon Hailemariam +1
Machine learning (ML) explainability is central to algorithmic transparency in high-stakes settings such as predictive diagnostics and loan approval. However, these same domains re…
DeepProv: Behavioral Characterization and Repair of Neural Networks via Inference Provenance Graph Analysis
Firas Ben Hmida, Abderrahmen Amich, Ata Kaboudi +1
Deep neural networks (DNNs) are increasingly being deployed in high-stakes applications, from self-driving cars to biometric authentication. However, their unpredictable and unreli…