Model Extraction of Convolutional Neural Networks with Max-Pooling

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Model extraction attacks aim to recover the internal parameters of neural networks through black-box queries. While significant progress has been achieved for fully connected ReLU networks, far less is known about structured architectures such as Convolutional Neural Networks (CNNs), which are widely used in practice. In particular, convolutional layers introduce locality and weight sharing, while max-pooling operations leak only relative activation information, both of which require rethinking