With the privatization deployment of DNNs on edge devices, the security of on-device DNNs has raised great concern. To quantify model leakage risk of on-device DNNs automatically, we propose NNReverse, the first learning-based method which can reverse DNNs from AI programs without domain knowledge. NNReverse trains a representation model to represent the semantic of binary codes for DNN layers. By searching the most similar function in our database, NNReverse infers the layer type of a given functions’ binary codes. To represent assembly instructions semantic precisely, NNReverse propose a more fine-grained embedding model to represent the textual and structural semantic of assembly functions.
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