Taesoo Kim

6.1k citations
138 papers · 3.8k indexed · h-index 39

Impact in

  • Software top 0.5%
    • Software Testing and Debugging Techniques
    • Advanced Malware Detection Techniques

Papers in

Taesoo Kim

128 papers receiving 3.6k citations

Peers

Taesoo Kim
Comparison fields: 5 of 82
  • Software 680
  • Signal Processing 1.8k
  • Hardware and Architecture 784
  • Artificial Intelligence 2.4k
  • Information Systems 1.4k
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Citations per field
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Citations per year

Countries citing papers authored by Taesoo Kim

Since Specialization
Citations

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

Fields of papers citing papers by Taesoo Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Taesoo Kim, 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 Taesoo Kim Line = papers co-authored together Taesoo Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20233
4
Automatic Techniques to Systematically Discover New Heap Exploitation Primitives
20207
5
{RAZOR}: A Framework for Post-deployment Software Debloating
201917
6
QSYM: a practical concolic execution engine tailored for hybrid fuzzing
2018166
7
LATR Lazy Translation Coherence
20181
8
Enabling refinable cross-host attack investigation with efficient data flow tagging and tracking
201816
9
Scaling Guest OS Critical Sections with eCS.
201811
10
Bunshin: compositing security mechanisms through diversification
20173
11
PlatPal: Detecting Malicious Documents with Platform Diversity
201713
12
Understanding manycore scalability of file systems
201647
13
Instant OS updates via userspace checkpoint-and-restart
201612
14
MetaSync: file synchronization across multiple untrusted storage services
201523
15 20141
16 20149
17
Practical and effective sandboxing for non-root users
201334
18 201218
19 201067
20
Making Linux protection mechanisms egalitarian with UserFS
201010

About Taesoo Kim

Taesoo Kim is a scholar working on Signal Processing, Software, Hardware and Architecture, Artificial Intelligence and Information Systems, having authored 138 papers that have together received 3.8k indexed citations. Recurring topics across this work include Security and Verification in Computing (60 papers), Advanced Malware Detection Techniques (57 papers), Parallel Computing and Optimization Techniques (22 papers), Software Testing and Debugging Techniques (20 papers), Distributed systems and fault tolerance (18 papers), Cloud Data Security Solutions (16 papers), Advanced Data Storage Technologies (15 papers) and Cloud Computing and Resource Management (10 papers). The work is most often cited by research in Software (680 citations), Signal Processing (1.8k citations), Hardware and Architecture (784 citations), Artificial Intelligence (2.4k citations) and Information Systems (1.4k citations). Taesoo Kim has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Sangho Lee, Marcus Peinado, Sanidhya Kashyap, Wenke Lee, Yeongjin Jang, Ming-Wei Shih, Byoungyoung Lee, Changwoo Min, Chengyu Song and Meng Xu. Their work appears in journals such as Physical Review A, IEEE/ACM Transactions on Networking, Journal of the Optical Society of America B, IEEE Access and IEEE Security & Privacy.

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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