Fetching the paper…
Reading the bibliography…
Recently, many profiling side-channel attacks based on Machine Learning and Deep Learning have been proposed.
Support-vector networks
Corinna Cortes and Vladimir Vapnik · 1995
Earlier work this paper cites.
Timing attacks on implementations of diffie-hellman, rsa, dss, and other systems
Paul C. Kocher · 1996
Earlier work this paper cites.
Multi-class support vector machines
Jason Weston and Chris Watkins · 1998
Earlier work this paper cites.
Differential power analysis
Paul C. Kocher, Joshua Jaffe, and Benjamin Jun · 1999
Earlier work this paper cites.
Random forests
Leo Breiman · 2001
Earlier work this paper cites.
Template attacks
Suresh Chari, Josyula R. Rao, and Pankaj Rohatgi · 2002
Earlier work this paper cites.
Best practices for convolutional neural networks applied to visual document analysis
Patrice Y. Simard, David Steinkraus, and John C. Platt · 2003
Earlier work this paper cites.
Correlation power analysis with a leakage model
Eric Brier, Christophe Clavier, and Francis Olivier · 2004
Earlier work this paper cites.
A stochastic model for differential side channel cryptanalysis
Werner Schindler, Kerstin Lemke, and Christof Paar · 2005
Earlier work this paper cites.
Mutual information analysis
Benedikt Gierlichs, Lejla Batina, Pim Tuyls, and Bart Preneel · 2008
Earlier work this paper cites.
An efficient method for random delay generation in embedded software
Jean-Sébastien Coron and Ilya Kizhvatov · 2009
Earlier work this paper cites.
A unified framework for the analysis of side-channel key recovery attacks
François-Xavier Standaert, Tal Malkin, and Moti Yung · 2009
Earlier work this paper cites.
Machine learning in side-channel analysis: a first study
Gabriel Hospodar, Benedikt Gierlichs, Elke De Mulder, Ingrid Verbauwhede, and Joos Vandewalle · 2011
Earlier work this paper cites.
Efficient template attacks based on probabilistic multi-class support vector machines
Timo Bartkewitz and Kerstin Lemke-Rust · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
Cited alongside, same era.
RSM: A small and fast countermeasure for aes, secure against 1st and 2nd-order zero-offset scas
Maxime Nassar, Youssef Souissi, Sylvain Guilley, and Jean-Luc Danger · 2012
Cited alongside, same era.
A machine learning approach against a masked AES
Liran Lerman, Stephane Fernandes Medeiros, Gianluca Bontempi, and Olivier Markowitch · 2013
Cited alongside, same era.
Rectifier nonlinearities improve neural network acoustic models
Andrew L Maas, Awni Y Hannun, and Andrew Y Ng · 2013
Cited alongside, same era.
Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
Data augmentation generative adversarial networks
Antreas Antoniou, Amos J. Storkey, and Harrison Edwards · 2017
Later among the works it cites.
Convolutional neural networks with data augmentation against jitter-based countermeasures - profiling attacks without pre-processing
Eleonora Cagli, Cécile Dumas, and Emmanuel Prouff · 2017
Later among the works it cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Later among the works it cites.
Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
Later among the works it cites.
Trace augmentation: What can be done even before preprocessing in a profiled sca?
Sihang Pu, Yu Yu, Weijia Wang, Zheng Guo, Junrong Liu, Dawu Gu, Lingyun Wang, and Jie Gan · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Power analysis attack: an approach based on machine learning
Liran Lerman, Gianluca Bontempi, and Olivier Markowitch · 2014
Cited alongside, same era.
Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Breaking cryptographic implementations using deep learning techniques
Houssem Maghrebi, Thibault Portigliatti, and Emmanuel Prouff · 2016
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
Cited alongside, same era.
Improved techniques for training gans
Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
Cited alongside, same era.
GAN augmentation: Augmenting training data using generative adversarial networks
Christopher Bowles, Liang Chen, Ricardo Guerrero, Paul Bentley, Roger N. Gunn, Alexander Hammers, David Alexander Dickie, Maria del C. Valdés Hernández, Joanna M. Wardlaw, and Daniel Rueckert · 2018
Later among the works it cites.
Synthetic data augmentation using GAN for improved liver lesion classification
Maayan Frid-Adar, Eyal Klang, Michal Amitai, Jacob Goldberger, and Hayit Greenspan · 2018
Later among the works it cites.
Study of deep learning techniques for side-channel analysis and introduction to ASCAD database
Emmanuel Prouff, Rémi Strullu, Ryad Benadjila, Eleonora Cagli, and Cécile Dumas · 2018
Later among the works it cites.
Make some noise. unleashing the power of convolutional neural networks for profiled side-channel analysis
Jaehun Kim, Stjepan Picek, Annelie Heuser, Shivam Bhasin, and Alan Hanjalic · 2019
Later among the works it cites.
Profiling side-channel analysis in the restricted attacker framework
Stjepan Picek, Annelie Heuser, and Sylvain Guilley · 2019
Later among the works it cites.
The curse of class imbalance and conflicting metrics with machine learning for side-channel evaluations
Stjepan Picek, Annelie Heuser, Alan Jovic, Shivam Bhasin, and Francesco Regazzoni · 2019
Later among the works it cites.
Non-profiled deep learning-based side-channel attacks with sensitivity analysis
Benjamin Timon · 2019
Later among the works it cites.