A comparative study of neural network techniques for automatic software vulnerability detection

no code implementations • 29 Apr 2021 • Gaigai Tang, Lianxiao Meng, Shuangyin Ren, Weipeng Cao, Qiang Wang, Lin Yang

To solve this problem, we have conducted extensive experiments to test the performance of the two most typical neural networks (i. e., Bi-LSTM and RVFL) with the two most classical data preprocessing methods (i. e., the vector representation and the program symbolization methods) on software vulnerability detection problems and obtained a series of interesting research conclusions, which can provide valuable guidelines for researchers and engineers.

Vulnerability Detection