DnD: A Cross-Architecture Deep Neural Network Decompiler
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Presented at USENIX Security 2022 by
The usage of Deep Neural Networks (DNNs) has steadily increased in recent years. Especially when used in edge devices, dedicated DNN compilers are used to compile DNNs into binaries. Many security applications (such as DNN model extraction, white-box adversarial sample generation, and DNN model patching and hardening) are possible when a DNN model is accessible. However, these techniques cannot be applied to compiled DNNs. Unfortunately, no dedicated decompiler exists that is able to recover a high-level representation of a DNN starting from its compiled binary code.