GCN DEVICE AND METHOD FOR LEARNING ASSEMBLY CODE AND DETECTING SOFTWARE WEAKNESS BASED ON GRAPH CONVOLUTION NETWORK

摘要

Disclosed is a learning device for generating a detection model that detects the presence or absence of security weaknesses in assembly code. The learning device corresponds to an assembly code constituting the learning data and generates a CFG (Control Flow Graph) composed of nodes and edges, and pre-sizes each of the nodes. And a vectorization unit that transforms into a predetermined corresponding matrix, and a learning unit that generates a detection model by learning a learning algorithm using a plurality of correspondence matrices and edge information each corresponding to one of the nodes.