BVSec develops cutting-edge artificial intelligence solutions for the automatic detection of software vulnerabilities and malware. Situated at the intersection of scientific research and industrial applications, the project leverages innovative binary file analysis techniques coupled with deep learning to enhance information system security. BVSec enables large-scale analysis efficiently, without the need to execute or decompile the code.
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- Some Recent Publications
- Karine Altisen, Marius Bozga: Revisited Convergence of a Self-stabilizing BFS Spanning Tree Algorithm
- Bruno Ferres, Oussama Oulkaid, Matthieu Moy, Gabriel Radanne, Ludovic Henrio, Pascal Raymond, Mehdi Khosravian: A Survey on Transistor-Level Electrical Rule Checking of Integrated Circuits
- Akram Idani, Yves Ledru, German Vega: Formal model-driven security combining B-method and process algebra: The B4MSecure platform
- Oussama Oulkaid, Bruno Ferres, Matthieu Moy, Pascal Raymond, Mehdi Khosravian: Modeling Techniques for the Formal Verification of Integrated Circuits at Transistor-Level: Performance Versus Precision Tradeoffs