1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2023
GraphMoco:a Graph Momentum Contrast Model that Using Multimodel Structure Information for Large-scale Binary Function Representation Learning
Sun Runjin, Guo ShiZe, Li Wei +3
In the field of cybersecurity, the ability to compute similarity scores at the function level is import. Considering that a single binary file may contain an extensive amount of fu…
cs.CR2022★ 1 cited
Instance Attack:An Explanation-based Vulnerability Analysis Framework Against DNNs for Malware Detection
Sun RuiJin, Guo ShiZe, Guo JinHong +4
Deep neural networks (DNNs) are increasingly being applied in malware detection and their robustness has been widely debated. Traditionally an adversarial example generation scheme…
cs.CR2022
SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings
Sun RuiJin, Guo Shize, Guo Jinhong +4
Function-level binary code similarity detection is a crucial aspect of cybersecurity. It enables the detection of bugs and patent infringements in released software and plays a piv…