Emmanuel Prouff

6.6k citations
31 papers · 917 · h-index 14

Impact in

Papers in

Emmanuel Prouff

29 papers receiving 878 citations

Peers

Emmanuel Prouff
Comparison fields: 5 of 71
  • Hardware and Architecture 481
  • Artificial Intelligence 786
  • Signal Processing 247
  • Computer Vision and Pattern Recognition 333
  • Information Systems 83
Replace Matthieu Rivain with:
Matthieu Rivain France
Bohan Yang Belgium
Mary Inaba Japan
Simon Heron Czechia
Zhihao Jia United States
Michael Perrone United States
Youngmin Yi South Korea
René Cumplido Mexico
Cong Fu China
Benedetta Tondi Italy
Emmanuel Prouff relative to Matthieu Rivain France Matthieu Rivain's profile →
Citations per field
00.5×1.5×2.4×
Matthieu Rivain · 1×
Citations per year

Countries citing papers authored by Emmanuel Prouff

Since Specialization
Citations

This map shows the geographic impact of Emmanuel Prouff's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emmanuel Prouff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emmanuel Prouff more than expected).

Fields of papers citing papers by Emmanuel Prouff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emmanuel Prouff. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emmanuel Prouff. The network helps show where Emmanuel Prouff may publish in the future.

Co-authors

The 25 scholars most cited alongside Emmanuel Prouff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Emmanuel Prouff Line = papers co-authored together Emmanuel Prouff links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010172
2 2019155
3 2009138
4 201185
5 201957
6 201951
7 201437
8 201632
9 201932
10 201217
11 201016
12 201415
13 201914
14 201213
15 201413
16 201710
17 20189
18 20138
19 20168
20 20097

About Emmanuel Prouff

Emmanuel Prouff is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Signal Processing and Electrical and Electronic Engineering, having authored 31 papers that have together received 917 indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (23 papers), Physical Unclonable Functions (PUFs) and Hardware Security (12 papers), Chaos-based Image/Signal Encryption (12 papers), Coding theory and cryptography (6 papers), Cryptography and Data Security (4 papers), Advanced Malware Detection Techniques (4 papers), Cryptography and Residue Arithmetic (2 papers) and Electromagnetic Compatibility and Noise Suppression (2 papers). The work is most often cited by research in Hardware and Architecture (481 citations), Artificial Intelligence (786 citations), Signal Processing (247 citations), Computer Vision and Pattern Recognition (333 citations) and Information Systems (83 citations). Emmanuel Prouff has collaborated with scholars based in France, Belgium and Australia. Frequent co-authors include Matthieu Rivain, Cécile Dumas, François‐Xavier Standaert, Régis Bevan, Eleonora Cagli, Ryad Benadjila, Nicolas Veyrat-Charvillon, Benedikt Gierlichs, Lejla Batina and Alexandre Venelli. Their work appears in journals such as Journal of Cryptographic Engineering, IACR Transactions on Cryptographic Hardware and Embedded Systems, IEEE Transactions on Computers, IEEE Transactions on Information Forensics and Security and Electronics Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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