Jieun Eom
Impact in
- Artificial Intelligence top 5%
- Cryptography and Data Security
- Privacy-Preserving Technologies in Data
- Cryptographic Implementations and Security
- Coding theory and cryptography
- Adversarial Robustness in Machine Learning
- Information Systems top 10%
- Cryptography and Residue Arithmetic
Papers in
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- Cryptography and Data Security 7
- Privacy-Preserving Technologies in Data 2
- Cryptographic Implementations and Security 2
- Coding theory and cryptography 2
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- Complexity and Algorithms in Graphs 3
- Co-authors
- Yongwoo Lee (3 shared papers)Maxim Deryabin (3 shared papers)Donghoon Yoo (2 shared papers)Junghyun Lee (1 shared paper)Jong‐Seon No (1 shared paper)Joon-Woo Lee (1 shared paper)Eunsang Lee (1 shared paper)HyungChul Kang (1 shared paper)
- Journals
- IEEE Access (2 papers)Journal of Medical Systems (1 paper)IEEE Transactions on Computers (1 paper)Lecture notes in computer science (2 papers)Information Security and Cryptology (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Jieun Eom
7 papers receiving 335 citations
Jieun Eom's Hit Papers
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 295
- Information Systems 89
- Health Informatics 5
- Computer Vision and Pattern Recognition 66
- Computational Theory and Mathematics 48
Countries citing papers authored by Jieun Eom
This map shows the geographic impact of Jieun Eom'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 Jieun Eom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jieun Eom more than expected).
Fields of papers citing papers by Jieun Eom
This network shows the impact of papers produced by Jieun Eom. 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 Jieun Eom. The network helps show where Jieun Eom may publish in the future.
Co-authors
The 16 scholars most cited alongside Jieun Eom, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Privacy-Preserving Machine Learning With Fully Homomorphic Encryption for Deep Neural Network Hit paper breakdown → | 2022 | 234 |
| 2 | 2023 | 48 | |
| 3 | 2023 | 32 | |
| 4 | 2016 | 19 | |
| 5 | 2018 | 11 | |
| 6 | 2018 | 2 | |
| 7 | Public Key Encryption with Keyword Search for Restricted Testability | 2011 | 1 |
About Jieun Eom
Jieun Eom is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Information Systems, having authored 7 papers that have together received 347 indexed citations. Recurring topics across this work include Cryptography and Data Security (7 papers), Complexity and Algorithms in Graphs (3 papers), Privacy-Preserving Technologies in Data (2 papers), Cryptographic Implementations and Security (2 papers), Coding theory and cryptography (2 papers), Chaos-based Image/Signal Encryption (2 papers), Cloud Data Security Solutions (1 paper) and Advanced Authentication Protocols Security (1 paper). The work is most often cited by research in Artificial Intelligence (295 citations), Information Systems (89 citations), Health Informatics (5 citations), Computer Vision and Pattern Recognition (66 citations) and Computational Theory and Mathematics (48 citations). Jieun Eom has collaborated with scholars based in South Korea and United States. Frequent co-authors include Yongwoo Lee, Maxim Deryabin, Donghoon Yoo, Junghyun Lee, Jong‐Seon No, Joon-Woo Lee, Eunsang Lee, HyungChul Kang, Young Sik Kim and Dong Hoon Lee. Their work appears in journals such as IEEE Access, Journal of Medical Systems, IEEE Transactions on Computers, Lecture notes in computer science and Information Security and Cryptology.
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.