Junbum Shin

896 citations
12 papers · 400 · h-index 8

Impact in

Papers in

    • Privacy-Preserving Technologies in Data 6
    • Cryptography and Data Security 4
    • Stochastic Gradient Optimization Techniques 3
    • Coding theory and cryptography 2
    • Cryptography and Residue Arithmetic 2

Junbum Shin

11 papers receiving 387 citations

Peers

Junbum Shin
Comparison fields: 5 of 42
  • Artificial Intelligence 336
  • Information Systems 206
  • Computer Science Applications 44
  • Transportation 33
  • Signal Processing 40
Replace Ricardo Mendes with:
Ricardo Mendes Portugal
Entong Shen United States
Michaela Götz United States
Alban Galland France
Ryan Skraba United Kingdom
Justin Brickell United States
Miguel A. Rueda-Morales Spain
Qiming Diao Singapore
Vincent Toubiana France
Junbum Shin relative to Ricardo Mendes Portugal Ricardo Mendes's profile →
Citations per field
00.5×10×
Ricardo Mendes · 1×
Citations per year

Countries citing papers authored by Junbum Shin

Since Specialization
Citations

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

Fields of papers citing papers by Junbum Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Junbum Shin, 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 Junbum Shin Line = papers co-authored together Junbum Shin links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2018150
2 201856
3 201850
4 201637
5 202131
6
Hardware-assisted on-demand hypervisor activation for efficient security critical code execution on mobile devices
201629
7 202124
8 201813
9 19986
10 20233
11 20241
12 20200

About Junbum Shin

Junbum Shin is a scholar working on Artificial Intelligence, Information Systems, Sociology and Political Science, Signal Processing and Management Science and Operations Research, having authored 12 papers that have together received 400 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (6 papers), Cryptography and Data Security (4 papers), Stochastic Gradient Optimization Techniques (3 papers), Privacy, Security, and Data Protection (3 papers), Advanced Malware Detection Techniques (2 papers), Coding theory and cryptography (2 papers), Cryptography and Residue Arithmetic (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Artificial Intelligence (336 citations), Information Systems (206 citations), Computer Science Applications (44 citations), Transportation (33 citations) and Signal Processing (40 citations). Junbum Shin has collaborated with scholars based in South Korea, United States and Singapore. Frequent co-authors include Sungwook Kim, Hyejin Shin, Xiaokui Xiao, Dongyoung Koo, Jinsu Kim, Kang G. Shin, Ning Wang, Ge Yu, Yin Yang and Hyunsoo Yoon. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Science China Information Sciences, Electronics Letters, ACM Transactions on Privacy and Security and Proceedings of the ACM on Programming Languages.

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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