GraphMoco:a Graph Momentum Contrast Model that Using Multimodel Structure Information for Large-scale Binary Function Representation Learning. (arXiv:2305.10826v1 [cs.CR])

The ability to compute similarity scores of binary code at the function level
is essential for cyber security. A single binary file can contain tens of
thousands of functions. A deployable learning framework for cybersecurity
applications needs to work not only accurately but also efficiently with large
amounts of data. Traditional methods suffer from two drawbacks. First, it is
very difficult to annotate different pairs of functions with accurate labels.
These supervised learning methods can easily be overtrained with inaccurate …

applications binary code compute cyber cyber security cybersecurity file framework function functions information large momentum representation scale security similarity single work