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pro vyhledávání: '"Jap, Dirmanto"'
Embedded devices with neural network accelerators offer great versatility for their users, reducing the need to use cloud-based services. At the same time, they introduce new security challenges in the area of hardware attacks, the most prominent bei
Externí odkaz:
http://arxiv.org/abs/2407.16467
Model extraction attacks have been widely applied, which can normally be used to recover confidential parameters of neural networks for multiple layers. Recently, side-channel analysis of neural networks allows parameter extraction even for networks
Externí odkaz:
http://arxiv.org/abs/2303.18132
EdgeML accelerators like Intel Neural Compute Stick 2 (NCS) can enable efficient edge-based inference with complex pre-trained models. The models are loaded in the host (like Raspberry Pi) and then transferred to NCS for inference. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2108.01281
Neural networks have been shown to be vulnerable against fault injection attacks. These attacks change the physical behavior of the device during the computation, resulting in a change of value that is currently being computed. They can be realized b
Externí odkaz:
http://arxiv.org/abs/2002.11021
Autor:
Alam, Manaar, Bag, Arnab, Roy, Debapriya Basu, Jap, Dirmanto, Breier, Jakub, Bhasin, Shivam, Mukhopadhyay, Debdeep
Neural Networks (NN) have recently emerged as backbone of several sensitive applications like automobile, medical image, security, etc. NNs inherently offer Partial Fault Tolerance (PFT) in their architecture; however, the biased PFT of NNs can lead
Externí odkaz:
http://arxiv.org/abs/1902.04560
Machine learning has become mainstream across industries. Numerous examples proved the validity of it for security applications. In this work, we investigate how to reverse engineer a neural network by using only power side-channel information. To th
Externí odkaz:
http://arxiv.org/abs/1810.09076
As deep learning systems are widely adopted in safety- and security-critical applications, such as autonomous vehicles, banking systems, etc., malicious faults and attacks become a tremendous concern, which potentially could lead to catastrophic cons
Externí odkaz:
http://arxiv.org/abs/1806.05859
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Publikováno v:
In Microelectronics Reliability May 2021 120
Akademický článek
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