Security Vulnerability Detection Method of Open-source Software Based on Graph Attention Network
With the popularity of open source software,software security problems are becoming increasingly prominent.The traditional vulnerability detection method has been unable to cope with today's complex virus vulnerabilities,and its detection results often have certain limitations.Therefore,the open source software security vulnerability detection method based on graph attention network is proposed.Firstly,the graph attention network model is constructed,and the source code detection is used as the entry point.Then,the vulnerability feature extraction of the open source software is used to realize the vulnerability identification and detection.In order to verify the performance of the graph attention network model in the proposed method,the model in this paper is compared with the Drebin algorithm.The results show that the graph attention network model can effectively detect the number of vulnerabilities in the open source software,and its maximum error value is 4,which has higher accuracy and efficiency compared with the security vulnerability detection method of Drebin algorithm.