Statistical Analysis of Second Order Differential Power Analysis
By Emmanuel Prouff, Matthieu Rivain, Régis Bevan. IEEE transactions on computers, 2009
333 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Hardware and Architecture, Signal Processing
View Paper: https://www.semanticscholar.org/paper/1eaaf7a5cda12c1aa03c300232dc935a2f6dd8af
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Emmanuel Prouff
- Houssem Maghrebi
- Thibault Portigliatti
- Sylvain Guilley
- Joshua Jaffe
- Claude Carlet
- Pankaj Rohatgi
- Paul C. Kocher
In Hardware and Architecture
- Emmanuel Prouff
- Houssem Maghrebi
- Thibault Portigliatti
- Joshua Jaffe
- Pankaj Rohatgi
- Paul C. Kocher
- Benjamin Jun
- Ankit Thakkar
In Signal Processing
Citations in the corpus
- Introduction to differential power analysis (2011, background): “Correlation power analysis (CPA) [ 37 ] involves evaluating the degree of correlation between variations within the set of measurements and a model of device leakage that depends on the value of (or a function of) one or more intermediates in the cryptographic calculation.”
- Complementary dual codes for counter-measures to side-channel attacks (2016, background): “Indeed, first-degree attacks consist in correlating the measured leakage with a leakage model, the latter being precisely independent of x, since equal to the expectation of φ(z) knowing x [22].”
- Breaking Cryptographic Implementations Using Deep Learning Techniques (2016, methodology): “a sigmoid) implicitly perform product combinations of the data samples which has as an effect the removal of the mask dependency(19) exactly like a second-order side channel attack [42].”