Network Identification

Network Identification refers to the process of identifying the internal parameter structure of a neural network by analyzing its input-output behavior. This task aims to reverse-engineer the neural network model to obtain its constituent parameters, thereby enabling model theft attacks. Network Identification not only helps in assessing the security of models but can also be used for model reproduction and optimization in specific scenarios, enhancing system performance and robustness. On the Methodology level, this task relies on advanced algorithms and technical means to ensure the accuracy and efficiency of parameter identification.