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Over the last decade, applications of neural networks (NNs) have spread to various aspects of our lives.
Visual feature extraction by a multilayered network of analog threshold elements
Kunihiko Fukushima · 1969
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Multilayer feedforward networks are universal approximators
Kurt Hornik, Maxwell Stinchcombe, and Halbert White · 1989
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Timing attacks on implementations of Diffie-Hellman, RSA, DSS, and other systems
Paul C. Kocher · 1996
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Soft Tempest: Hidden data transmission using electromagnetic emanations
Markus G. Kuhn and Ross J. Anderson · 1998
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Differential power analysis
Paul Kocher, Joshua Jaffe, and Benjamin Jun · 1999
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On Boolean and arithmetic masking against differential power analysis
Jean-Sébastien Coron and Louis Goubin · 2000
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Electromagnetic analysis (EMA): measures and counter-measures for smart cards
Jean-Jacques Quisquater and David Samyde · 2001
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Correlation power analysis with a leakage model
Eric Brier, Christophe Clavier, and Francis Olivier · 2004
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High performance convolutional neural networks for document processing
Kumar Chellapilla, Sidd Puri, and Patrice Simard · 2006
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Power analysis attacks: Revealing the secrets of smart cards
Stefan Mangard, Elisabeth Oswald, and Thomas Popp · 2008
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Formulas for robust, one-pass parallel computation of covariances and arbitrary-order statistical moments
Philippe Pierre Pébay · 2008
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Recognition of electro-magnetic leakage information from computer radiation with SVM
Zhang Hongxin, Huang Yuewang, Wang Jianxin, Lu Yinghua, and Zhang Jinling · 2009
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Horizontal correlation analysis on exponentiation
Christophe Clavier, Benoit Feix, Georges Gagnerot, Mylène Roussellet, and Vincent Verneuil · 2010
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A testing methodology for side-channel resistance validation
Benjamin Jun Gilbert Goodwill, Josh Jaffe, Pankaj Rohatgi, et al · 2011
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Improving differential power analysis by elastic alignment
Jasper G. J. van Woudenberg, Marc F. Witteman, and Bram Bakker · 2011
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Realistic eavesdropping attacks on computer displays with low-cost and mobile receiver system
Fürkan Elibol, Uğur Sarac, and Işin Erer · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Shuffling against side-channel attacks: A comprehensive study with cautionary note
Nicolas Veyrat-Charvillon, Marcel Medwed, Stéphanie Kerckhof, and François-Xavier Standaert · 2012
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Min Lin, Qiang Chen, and Shuicheng Yan · 2013
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Masking against side-channel attacks: A formal security proof
Emmanuel Prouff and Matthieu Rivain · 2013
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Leakage assessment methodology
Tobias Schneider and Amir Moradi · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Binarized neural networks
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 2016
Cited alongside, same era.
Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
Cited alongside, same era.
Time-series extreme event forecasting with neural networks at uber
Nikolay Laptev, Jason Yosinski, Li Erran Li, and Slawek Smyl · 2017
Cited alongside, same era.
Mixed precision training
Sharan Narang, Gregory Diamos, Erich Elsen, Paulius Micikevicius, Jonah Alben, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, et al · 2017
Cited alongside, same era.
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
On reverse engineering neural network implementation on GPU
Łukasz Chmielewski and Léo Weissbart · 2021
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Screen gleaning: A screen reading TEMPEST attack on mobile devices exploiting an electromagnetic side channel
Zhuoran Liu, Niels Samwel, Léo Weissbart, Zhengyu Zhao, Dirk Lauret, Lejla Batina, and Martha Larson · 2021
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Extraction of binarized neural network architecture and secret parameters using side-channel information
Ville Yli-Mäyry, Akira Ito, Naofumi Homma, Shivam Bhasin, and Dirmanto Jap · 2021
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Accessed: 2022-01-25
https://www.langer-emv.de/en/product/mfa-active-1mhz-up-to-6-ghz/32/mfa-r-0-2-75-near-field-micro-probe-1-mhz-up-to-1-ghz/854 · 2022
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Accessed: 2022-11-30
https://developer.download.nvidia.com/CUDA/training/StreamsAndConcurrencyWebinar.pdf · 2022
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https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#context
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David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, et al · 2017
Cited alongside, same era.
Leakage detection with the x2-test
Amir Moradi, Bastian Richter, Tobias Schneider, and François-Xavier Standaert · 2018
Cited alongside, same era.
Pieces of eight: 8-bit neural machine translation
Jerry Quinn and Miguel Ballesteros · 2018
Cited alongside, same era.
Deep state space models for time series forecasting
Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, and Tim Januschowski · 2018
Cited alongside, same era.
CSI–NN: Reverse engineering of neural network architectures through electromagnetic side channel
Lejla Batina, Shivam Bhasin, Dirmanto Jap, and Stjepan Picek · 2019
Cited alongside, same era.
Scniffer: Low-cost, automated, efficient electromagnetic side-channel sniffing
Josef Danial, Debayan Das, Santosh K. Ghosh, Arijit Raychowdhury, and Shreyas Sen · 2019
Cited alongside, same era.
Deep learning for audio signal processing
Hendrik Purwins, Bo Li, Tuomas Virtanen, Jan Schlüter, Shuo-Yiin Chang, and Tara Sainath · 2019
Cited alongside, same era.
Cuda Context · 2022
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https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#programming-model
CUDA programming model · 2022
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https://docs.nvidia.com/cuda/cuda-binary-utilities/#usage
cuobjdump · 2022
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https://github.com/Riscure/Jlsca
Jlsca · 2022
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https://developer.nvidia.com/embedded/jetson-nano-developer-kit
NVIDIA Jetson Nano · 2022
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https://docs.nvidia.com/cuda/cuda-c-programming-guide/#simt-architecture
SIMT architecture · 2022
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http://international.download.nvidia.com/pdf/tegra/Tegra-X1-whitepaper-v1.0.pdf
Tegra X1 System-On-Chip · 2022
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https://docs.xilinx.com/v/u/en-US/ds187-XC7Z010-XC7Z020-Data-Sheet
ZYNQ Data Sheet · 2022
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A practical introduction to side-channel extraction of deep neural network parameters
Raphaël Joud, Pierre-Alain Moëllic, Simon Pontié, and Jean-Baptiste Rigaud · 2022
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Power-based attacks on spatial DNN accelerators
Ge Li, Mohit Tiwari, and Michael Orshansky · 2022
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Can one hear the shape of a neural network?: Snooping the GPU via magnetic side channel
Henrique Teles Maia, Chang Xiao, Dingzeyu Li, Eitan Grinspun, and Changxi Zheng · 2022
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Paulius Micikevicius, Dusan Stosic, Neil Burgess, Marius Cornea, Pradeep Dubey, Richard Grisenthwaite, Sangwon Ha, Alexander Heinecke, Patrick Judd, John Kamalu, Naveen Mellempudi, Stuart Oberman, Mohammad Shoeybi, Michael Siu, and Hao Wu · 2022
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Accessed: 2023-03-25
https://www.langer-emv.de/en/product/rf-passive-30-mhz-up-to-3-ghz/35/rf-b-0-3-3-h-field-probe-mini-30-mhz-up-to-3-ghz/17 · 2023
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https://developer.nvidia.com/downloads/assets/embedded/secure/jetson/orin_nano/docs/jetson_orin_nano_ds
Jetso orin nano module · 2024
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Side-channel-assisted reverse-engineering of encrypted DNN hardware accelerator IP and attack surface exploration
Cheng Gongye, Yukui Luo, Xiaolin Xu, and Yunsi Fei · 2024
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CNN architecture extraction on edge GPU
Peter Horvath, Lukasz Chmielewski, Leo Weissbart, Lejla Batina, and Yuval Yarom · 2024
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