KEYWORDS: Data modeling, Visualization, Visual process modeling, Software development, Human-machine interfaces, Systems modeling, Statistical modeling, Data visualization, Analytical research
A visualization system with source code vulnerability detection is constructed based on the deep learning BLSTM model. The system firstly has the static analysis and slicing capabilities of the vulnerability statement, and then based on the deep learning model of the recurrent neural network and the attention mechanism technology, it can learn from the vulnerability data set the characteristics of the vulnerability and the realization of vulnerability detection. Firstly, the system analyzes the source code through the deployed open-source static analysis tool Joern according to the code to be tested, and stores the generated code attribute graph in the Neo4J graph database, then slices the program code according to the API call. The sliced code is treated as a text, which is mapped into a vector using word embedding technology, and finally input into the BLSTM model to determine whether there is vulnerability in the code under test. Through the visual interface, the system can interact with the user, and the user can independently select and train the model. Through experimental analysis and testing, the system has achieved good results.
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