D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 33 Citations 5,584 80 World Ranking 6703 National Ranking 166

Overview

What is he best known for?

The fields of study he is best known for:

  • Algorithm
  • Algebra
  • Cryptography

Emmanuel Prouff spends much of his time researching Side channel attack, Algorithm, Block cipher, Power analysis and Theoretical computer science. His Side channel attack study is concerned with the larger field of Cryptography. Algorithm and Masking are two areas of study in which Emmanuel Prouff engages in interdisciplinary research.

His study explores the link between Block cipher and topics such as Security parameter that cross with problems in Masking, Computer engineering, Countermeasure, Order and Multiplication. The various areas that Emmanuel Prouff examines in his Power analysis study include Adversary, Mutual information and Data mining. Emmanuel Prouff has included themes like Deep learning, Artificial intelligence and Computation in his Theoretical computer science study.

His most cited work include:

  • Provably secure higher-order masking of AES (337 citations)
  • Statistical Analysis of Second Order Differential Power Analysis (230 citations)
  • Masking against Side-Channel Attacks: A Formal Security Proof (174 citations)

What are the main themes of his work throughout his whole career to date?

Emmanuel Prouff mainly focuses on Side channel attack, Cryptography, Algorithm, Block cipher and Theoretical computer science. His research in Side channel attack intersects with topics in Exploit, Masking, Computer engineering and Power analysis. His Cryptography study combines topics in areas such as Function and Hamming distance.

His work on Correlation attack as part of general Algorithm study is frequently linked to Masking, First order and Hamming weight, therefore connecting diverse disciplines of science. His research integrates issues of Computation, Arithmetic, Security parameter and Implementation in his study of Block cipher. His biological study deals with issues like Adversary, which deal with fields such as Mathematical proof.

He most often published in these fields:

  • Side channel attack (52.59%)
  • Cryptography (31.11%)
  • Algorithm (28.15%)

What were the highlights of his more recent work (between 2017-2021)?

  • Side channel attack (52.59%)
  • Artificial intelligence (8.89%)
  • Deep learning (5.93%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Side channel attack, Artificial intelligence, Deep learning, Implementation and Randomness. In his research, he undertakes multidisciplinary study on Side channel attack and Singular spectrum analysis. His work on Artificial neural network, Preprocessor and Independent component analysis as part of general Artificial intelligence research is often related to Blind signal separation and Signal processing, thus linking different fields of science.

His Deep learning research is multidisciplinary, incorporating elements of Computer security and Information retrieval. The Implementation study combines topics in areas such as Adversary, Mathematical proof and Theoretical computer science. His study in Randomness is interdisciplinary in nature, drawing from both Discrete mathematics, Multiplicative function, Computation and Block cipher.

Between 2017 and 2021, his most popular works were:

  • Study of Deep Learning Techniques for Side-Channel Analysis and Introduction to ASCAD Database. (70 citations)
  • Deep Learning to Evaluate Secure RSA Implementations (20 citations)
  • A Comprehensive Study of Deep Learning for Side-Channel Analysis (18 citations)

In his most recent research, the most cited papers focused on:

  • Algebra
  • Algorithm
  • Cryptography

Emmanuel Prouff mainly investigates Deep learning, Artificial intelligence, Side channel attack, Context and Information retrieval. Emmanuel Prouff has included themes like Computer security and Open platform in his Artificial intelligence study. Computer security is closely attributed to Implementation in his research.

His work carried out in the field of Open platform brings together such families of science as Cryptography, Convolutional neural network and Database. His Visualization research includes elements of Artificial neural network and Information leakage. His Upper and lower bounds research includes elements of Mutual information, Soundness, Theoretical computer science and Entropy.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Provably secure higher-order masking of AES

Matthieu Rivain;Emmanuel Prouff.
cryptographic hardware and embedded systems (2010)

467 Citations

Statistical Analysis of Second Order Differential Power Analysis

Emmanuel Prouff;Matthieu Rivain;Régis Bevan.
IEEE Transactions on Computers (2009)

298 Citations

Masking against Side-Channel Attacks: A Formal Security Proof

Emmanuel Prouff;Matthieu Rivain.
theory and application of cryptographic techniques (2013)

266 Citations

Breaking Cryptographic Implementations Using Deep Learning Techniques

Houssem Maghrebi;Thibault Portigliatti;Emmanuel Prouff.
Space (2016)

248 Citations

Mutual Information Analysis: a Comprehensive Study

Lejla Batina;Benedikt Gierlichs;Emmanuel Prouff;Matthieu Rivain.
Journal of Cryptology (2011)

242 Citations

Convolutional Neural Networks with Data Augmentation Against Jitter-Based Countermeasures

Eleonora Cagli;Eleonora Cagli;Cécile Dumas;Emmanuel Prouff.
cryptographic hardware and embedded systems (2017)

195 Citations

DPA attacks and s-boxes

Emmanuel Prouff.
fast software encryption (2005)

178 Citations

Univariate side channel attacks and leakage modeling

Julien Doget;Emmanuel Prouff;Matthieu Rivain;François-Xavier Standaert.
Journal of Cryptographic Engineering (2011)

177 Citations

Privacy-Preserving Classification on Deep Neural Network.

Hervé Chabanne;Amaury de Wargny;Jonathan Milgram;Constance Morel.
IACR Cryptology ePrint Archive (2017)

173 Citations

Study of Deep Learning Techniques for Side-Channel Analysis and Introduction to ASCAD Database.

Emmanuel Prouff;Rémi Strullu;Ryad Benadjila;Eleonora Cagli.
IACR Cryptology ePrint Archive (2018)

140 Citations

Best Scientists Citing Emmanuel Prouff

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Sylvain Guilley

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François-Xavier Standaert

François-Xavier Standaert

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Claude Carlet

Claude Carlet

Paris 8 University

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Lejla Batina

Lejla Batina

Radboud University Nijmegen

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Elisabeth Oswald

Elisabeth Oswald

University of Klagenfurt

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Debdeep Mukhopadhyay

Debdeep Mukhopadhyay

Indian Institute of Technology Kharagpur

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Tim Güneysu

Tim Güneysu

Ruhr University Bochum

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Thomas Eisenbarth

Thomas Eisenbarth

University of Lübeck

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Patrick Schaumont

Patrick Schaumont

Worcester Polytechnic Institute

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Jean-Sébastien Coron

Jean-Sébastien Coron

University of Luxembourg

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Vincent Rijmen

Vincent Rijmen

KU Leuven

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Pierre-Alain Fouque

Pierre-Alain Fouque

University of Rennes 1

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Ingrid Verbauwhede

Ingrid Verbauwhede

KU Leuven

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Stefan Mangard

Stefan Mangard

Graz University of Technology

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Chao Wang

Chao Wang

Chinese Academy of Sciences

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Stefan Dziembowski

Stefan Dziembowski

University of Warsaw

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Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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