Masaya Yasuda

23 papers receiving 170 citations

Peers

Masaya Yasuda
Comparison fields: 5 of 32
  • Artificial Intelligence 137
  • Computational Theory and Mathematics 59
  • Information Systems 53
  • Computer Vision and Pattern Recognition 33
  • Signal Processing 26
Replace Wilko Henecka with:
Wilko Henecka Australia
Jun Kogure Japan
Jacob C. N. Schuldt Japan
Jakob Pagter Denmark
Shigeo Mitsunari Japan
Markus Jakobsson United States
Benne de Weger Netherlands
Mehdi Tibouchi Japan
Omer Paneth United States
Khoa Nguyen Singapore
Masaya Yasuda relative to Wilko Henecka Australia Wilko Henecka's profile →
Citations per field
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Wilko Henecka · 1×
Citations per year

Countries citing papers authored by Masaya Yasuda

Since Specialization
Citations

This map shows the geographic impact of Masaya Yasuda'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 Masaya Yasuda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masaya Yasuda more than expected).

Fields of papers citing papers by Masaya Yasuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Masaya Yasuda. 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 Masaya Yasuda. The network helps show where Masaya Yasuda may publish in the future.

Co-authorship network of co-authors of Masaya Yasuda

This figure shows the co-authorship network connecting the top 25 collaborators of Masaya Yasuda. A scholar is included among the top collaborators of Masaya Yasuda based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Masaya Yasuda. Masaya Yasuda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 4
4 1
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6 3
7
Privacy-preserving fuzzy commitment for biometrics via layered error-correcting codes
0
8 0
9
A biometric key-binding scheme using lattice masking
1
10 1
11
A proposal of key binding technology using lattice masking
1
12 61
13 0
14
A generalization of the anomalous attack for the ECDLP over Q p
1
15
Experimental Analysis of Cheon's Algorithm against Pairing-friendly Curves (特集 人と共存するコンピュータセキュリティ技術)
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16 0
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THE LIFTING PROBLEM FOR THE ECDLP AND THE SELMER RANK
1
18 0
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On random walks of Pollard's rho method for the ECDLP on Koblitz curves
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20
Schauder Expansion by some Quadratic Base Function
4

About Masaya Yasuda

Masaya Yasuda is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics, having authored 33 papers that have together received 174 indexed citations. Recurring topics across this work include Cryptography and Data Security (21 papers), Cryptography and Residue Arithmetic (12 papers) and Coding theory and cryptography (11 papers). The work is most often cited by research in Artificial Intelligence (137 citations), Computational Theory and Mathematics (59 citations) and Signal Processing (26 citations). Masaya Yasuda has collaborated with scholars based in Japan, Australia and Bulgaria. Frequent co-authors include Takeshi Shimoyama, Jun Kogure, Takeshi Koshiba, Kazuhiro Yokoyama, Pradeep Kumar Mishra, Dung Hoang Duong, Deevashwer Rathee, Tetsuya Izu, Tsuyoshi Takagi and Satoshi Nakamura. Their work appears in journals such as Lecture notes in computer science, Discrete Applied Mathematics and Designs Codes and Cryptography.

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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