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Showing 1 to 2 of 2 for “"Secure DNN"”.
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Converting Autoencoder Based Energy-Efficient and Secure DNN Inference on Edge Devices
Deep neural networks (DNNs) have become essential for computer vision tasks like image classification, object detection, and depth estimation. With the rise of embedded devices, there is a growing demand for lightweight and energy-efficient models. While DNNs outperform traditional machine learning …
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Towards Secure Machine Learning Acceleration: Threats and Defenses Across Algorithms, Architecture, and Circuits
As deep neural networks (DNNs) are widely adopted for high-stakes applications that process sensitive private data and make critical decisions, security concerns about user data and DNN models are growing. In particular, hardware-level vulnerabilities can be exploited to undermine the …