Sang C. Suh
- Artificial Intelligence top 2%
- Computer Networks and Communications top 2%
- Signal Processing top 2%
- Control and Systems Engineering top 10%
- Information Systems top 10%
- Co-authors
- Jinoh KimHyunjoo KimDonghwoon KwonIkkyun KimKuinam J. KimU. John TanikAbdullah EroğluJonghyun Kim
- Topics
- Network Security and Intrusion Detection (13 papers)Internet Traffic Analysis and Secure E-voting (9 papers)Anomaly Detection Techniques and Applications (9 papers)
- Partner nations
- United StatesSouth KoreaUnited Kingdom
In The Last Decade
Sang C. Suh
34 papers receiving 868 citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 653
- Computer Networks and Communications 596
- Signal Processing 280
- Control and Systems Engineering 97
- Information Systems 97
Countries citing papers authored by Sang C. Suh
This map shows the geographic impact of Sang C. Suh'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 Sang C. Suh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sang C. Suh more than expected).
Fields of papers citing papers by Sang C. Suh
This network shows the impact of papers produced by Sang C. Suh. 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 Sang C. Suh. The network helps show where Sang C. Suh may publish in the future.
Co-authorship network of co-authors of Sang C. Suh
This figure shows the co-authorship network connecting the top 25 collaborators of Sang C. Suh. A scholar is included among the top collaborators of Sang C. Suh 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 Sang C. Suh. Sang C. Suh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 96 | |
| 6 | 41 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | A survey of deep learning-based network anomaly detectionbreakdown → | 506 |
| 10 | 5 | |
| 11 | 10 | |
| 12 | 14 | |
| 13 | 1 | |
| 14 | 2 | |
| 15 | The role of conceptual hierarchies in the diagnosis and prevention of diabetes | 2 |
| 16 | 1 | |
| 17 | 6 | |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 2 |
About Sang C. Suh
Sang C. Suh is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems, having authored 36 papers that have together received 914 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (13 papers), Internet Traffic Analysis and Secure E-voting (9 papers) and Anomaly Detection Techniques and Applications (9 papers). The work is most often cited by research in Computer Networks and Communications (596 citations), Signal Processing (280 citations) and Artificial Intelligence (653 citations). Sang C. Suh has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Jinoh Kim, Hyunjoo Kim, Donghwoon Kwon, Ikkyun Kim, Kuinam J. Kim, U. John Tanik, Abdullah Eroğlu, Jonghyun Kim, Taejoon Kim and Alex Sim. Their work appears in journals such as IEEE Access, Journal of Medical Systems and Computing.
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.