Rakyong Choi
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Information Systems
- Computer Vision and Pattern Recognition
- Co-authors
- Kwangjo KimHarry Chandra TanuwidjajaMuhamad Erza AminantoPaul D. YooMaxim DeryabinJieun EomYongwoo LeeDong-Hoon Yoo
- Topics
- Cryptography and Data Security (6 papers)Privacy-Preserving Technologies in Data (3 papers)Complexity and Algorithms in Graphs (3 papers)
- Journals
- IEEE AccessIEEE Transactions on ComputersIEEE Transactions on Information Forensics and Security
- Partner nations
- South KoreaUnited Kingdom
In The Last Decade
Rakyong Choi
10 papers receiving 261 citations
Peers
Comparison fields: 5 of 43
- Artificial Intelligence 202
- Computer Networks and Communications 155
- Signal Processing 73
- Information Systems 43
- Computer Vision and Pattern Recognition 32
Countries citing papers authored by Rakyong Choi
This map shows the geographic impact of Rakyong Choi'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 Rakyong Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rakyong Choi more than expected).
Fields of papers citing papers by Rakyong Choi
This network shows the impact of papers produced by Rakyong Choi. 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 Rakyong Choi. The network helps show where Rakyong Choi may publish in the future.
Co-authorship network of co-authors of Rakyong Choi
This figure shows the co-authorship network connecting the top 25 collaborators of Rakyong Choi. A scholar is included among the top collaborators of Rakyong Choi 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 Rakyong Choi. Rakyong Choi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 73 | |
| 3 | 7 | |
| 4 | Limitations of privacy-preserving for confidential data training by deep learning | 2 |
| 5 | AtLast: Another Three-party Lattice-based PAKE Scheme | 3 |
| 6 | Performance evaluation of liboqs in Open Quantum Safe project (Part I) | 1 |
| 7 | Prey on Lizard: Mining Secret Key on Lattice-based Cryptosystem | 0 |
| 8 | Security analysis of end-to-end encryption in Telegram | 5 |
| 9 | 158 | |
| 10 | Lattice-based Multi-signature with Linear Homomorphism | 2 |
| 11 | Lattice-based Threshold Signature with Message Block Sharing | 2 |
About Rakyong Choi
Rakyong Choi is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Geometry and Topology, having authored 11 papers that have together received 270 indexed citations. Recurring topics across this work include Cryptography and Data Security (6 papers), Privacy-Preserving Technologies in Data (3 papers) and Complexity and Algorithms in Graphs (3 papers). The work is most often cited by research in Signal Processing (73 citations), Computer Networks and Communications (155 citations) and Artificial Intelligence (202 citations). Rakyong Choi has collaborated with scholars based in South Korea and United Kingdom. Frequent co-authors include Kwangjo Kim, Harry Chandra Tanuwidjaja, Muhamad Erza Aminanto, Paul D. Yoo, Maxim Deryabin, Jieun Eom, Yongwoo Lee, Dong-Hoon Yoo and Kwangjo Kim. Their work appears in journals such as IEEE Access, IEEE Transactions on Computers and IEEE Transactions on Information Forensics and Security.
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.