Mutual Information Analysis
By Benedikt Gierlichs, Lejla Batina, Pim Tuyls, Bart Preneel. Workshop on Cryptographic Hardware and Embedded Systems, 2008
660 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Hardware and Architecture
View Paper: https://www.semanticscholar.org/paper/fb915ec557aed210538e98ef8025832329ec4459
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
- Svetla Nikova
- Vincent Rijmen
- Martin Schläffer
- Axel York Poschmann
- Christof Paar
In Hardware and Architecture
- Houssem Maghrebi
- Thibault Portigliatti
- Svetla Nikova
- Vincent Rijmen
- Emmanuel Prouff
- Martin Schläffer
- Ankit Thakkar
- Ritika Lohiya
Citations in the corpus
- Breaking Cryptographic Implementations Using Deep Learning Techniques (2016, background): “The set of non-profiled attacks includes Differential Power Analysis (DPA) [30], Correlation Power Analysis (CPA) [9] and Mutual Information Analysis (MIA) [20].”
- I Know What You See: Power Side-Channel Attack on Convolutional Neural Network Accelerators (2018, neutral): “devices. By analyzing the difference of multiple power traces with diverse inputs, attackers are able to uncover the secret key in widely used symmetric encryption standards, such as DES [17] and AES [3, 9, 23]. Eisenbarth [6] and Msgna [25] showed they can recover the instruction type executed by p”
- Secure Hardware Implementation of Nonlinear Functions in the Presence of Glitches (2011, background): “Indeed, mutual information analysis can lead to better side-channel attacks if the measured statistical leakage L(t) is related to the hypothesis H(k) in a nonlinear way [29,40].”