A Stochastic Model for Differential Side Channel Cryptanalysis

By W. Schindler, Kerstin Lemke-Rust, Christof Paar. Workshop on Cryptographic Hardware and Embedded Systems, 2005

582 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/beba132e54ed675fddf6914deda10af20a481ae4

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Citations in the corpus

Statistical Analysis of Second Order Differential Power Analysis (2009, methodology): “For further information about Profiling SCA, the different studies conducted, for instance, in [2], [3], [4] may be read.”
Convolutional Neural Networks with Data Augmentation Against Jitter-Based Countermeasures - Profiling Attacks Without Pre-processing (2017, methodology): “For the template processing, we tried (1) the classical approach [5] where a mean and a covariance matrix are estimated for each class, (2) the pooled covariance matrix strategy proposed in [6] and (3) the stochastic approach proposed in [28].”
Introduction to differential power analysis (2011, background): “exist, the stochastic approach [53] can be a much more efficient alternative to template attacks.”
Deep learning for side-channel analysis and introduction to ASCAD database (2019, methodology): “It includes templates attacks [14] and Stochastic modelling (a.k.a. linear regression analysis) [17,58,59].”
Breaking Cryptographic Implementations Using Deep Learning Techniques (2016, background): “The set of profiled attacks includes Template attacks [10] and Stochastic cryptanalyses (aka Linear Regression Analyses) [16,47,48].”
Introduction to Side-Channel Attacks (2010, background): “…advantage of multivariate statistics, either by using the so-called “higher-order” attacks [15] or by considering optimal strategies such as template attacks [6] or stochastic models [22] (which generally require to characterize the device leakage prior to the actual application of the attack).”
A Unified Framework for the Analysis of Side-Channel Key Recovery Attacks (extended version) (2009, methodology): “The data dimensionality reduction techniques used in [4, 35] and the stochastic models in [17, 31] can be used to answer these questions in a systematic manner.”