Vulnerability Detection Method Based on Word Vector Model

Abstract

Aiming at the problems of non-uniform experimental platforms and heterogeneous datasets faced in the field of vulnerability detection, we studied the application of word vector models in C/C + +function vulnerability detection. Five word vector models were used for the knowledge representation of the abstract syntax tree structure generated by the source code, and six neural network models were used for vulnerability detection. The experimental results show that functionlevel code has shallow semantic relationships and tight connections within code blocks.