Figure 4
From: Recurrent quantum embedding neural network and its application in vulnerability detection
Vulnerability detection task flow. We extract normalized labeled code gadgets from the source code as training data and then generate parameterized binary indexes from them, which are fed into the RQENN classifier. After training, the model can detect the presence of vulnerabilities in the source code.
