Insu Yun

859 total citations
17 papers, 557 citations indexed

About

Insu Yun is a scholar working on Signal Processing, Artificial Intelligence and Software. According to data from OpenAlex, Insu Yun has authored 17 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Signal Processing, 9 papers in Artificial Intelligence and 7 papers in Software. Recurrent topics in Insu Yun's work include Advanced Malware Detection Techniques (9 papers), Security and Verification in Computing (7 papers) and Software Testing and Debugging Techniques (7 papers). Insu Yun is often cited by papers focused on Advanced Malware Detection Techniques (9 papers), Security and Verification in Computing (7 papers) and Software Testing and Debugging Techniques (7 papers). Insu Yun collaborates with scholars based in United States, South Korea and Israel. Insu Yun's co-authors include Taesoo Kim, Yeongjin Jang, Sang-Ho Lee, Meng Xu, Muhammad Asim Jamshed, Yung Yi, Sangwoo Moon, KyoungSoo Park, Wen Xu and Hyungon Moon and has published in prestigious journals such as IEEE/ACM Transactions on Networking, Operating Systems Design and Implementation and Scholarworks@UNIST (Ulsan National Institute of Science and Technology).

In The Last Decade

Insu Yun

14 papers receiving 529 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Insu Yun United States 9 280 248 238 215 169 17 557
Robert Gawlik Germany 9 530 1.9× 354 1.4× 342 1.4× 154 0.7× 309 1.8× 14 716
Lorenzo Martignoni Italy 13 573 2.0× 358 1.4× 344 1.4× 280 1.3× 290 1.7× 17 750
Daniel Lehmann Germany 9 222 0.8× 261 1.1× 117 0.5× 122 0.6× 170 1.0× 13 404
Purui Su China 11 286 1.0× 319 1.3× 160 0.7× 228 1.1× 217 1.3× 54 577
Asia Slowinska Netherlands 13 648 2.3× 589 2.4× 197 0.8× 323 1.5× 290 1.7× 23 834
Lucian Cojocar Netherlands 5 307 1.1× 240 1.0× 304 1.3× 79 0.4× 166 1.0× 6 545
Matthew Harren United States 6 202 0.7× 474 1.9× 122 0.5× 281 1.3× 161 1.0× 9 620
Haogang Chen China 11 236 0.8× 398 1.6× 95 0.4× 356 1.7× 247 1.5× 16 645
Brad Chen United States 5 170 0.6× 218 0.9× 44 0.2× 208 1.0× 181 1.1× 6 415
John Criswell United States 13 401 1.4× 579 2.3× 106 0.4× 376 1.7× 313 1.9× 35 912

Countries citing papers authored by Insu Yun

Since Specialization
Citations

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

Fields of papers citing papers by Insu Yun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Insu Yun

This figure shows the co-authorship network connecting the top 25 collaborators of Insu Yun. A scholar is included among the top collaborators of Insu Yun 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 Insu Yun. Insu Yun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
2.
Park, Junyoung, Yunho Kim, & Insu Yun. (2025). RGFuzz: Rule-Guided Fuzzer for WebAssembly Runtimes. 920–938.
3.
4.
Yun, Insu, et al.. (2022). Fuzzing@Home: Distributed Fuzzing on Untrusted Heterogeneous Clients. 1–16. 2 indexed citations
5.
Yun, Insu, et al.. (2022). Scalable and Secure Virtualization of HSM With ScaleTrust. IEEE/ACM Transactions on Networking. 31(4). 1595–1610. 4 indexed citations
6.
Hu, Hong, et al.. (2021). Preventing Use-After-Free Attacks with Fast Forward Allocation. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2453–2470. 8 indexed citations
7.
8.
Yun, Insu, et al.. (2021). HardsHeap: A Universal and Extensible Framework for Evaluating Secure Allocators. 379–392. 5 indexed citations
9.
Yun, Insu, et al.. (2020). Automatic Techniques to Systematically Discover New Heap Exploitation Primitives. USENIX Security Symposium. 1111–1128. 7 indexed citations
10.
Park, Soyeon, et al.. (2020). Fuzzing JavaScript Engines with Aspect-preserving Mutation. 1629–1642. 49 indexed citations
11.
Yun, Insu, Sang-Ho Lee, Meng Xu, Yeongjin Jang, & Taesoo Kim. (2018). QSYM: a practical concolic execution engine tailored for hybrid fuzzing. USENIX Security Symposium. 745–761. 166 indexed citations
12.
Cui, Weidong, Xinyang Ge, Baris Kasikci, et al.. (2018). REPT: reverse debugging of failures in deployed software. Operating Systems Design and Implementation. 17–32. 26 indexed citations
13.
Yun, Insu, et al.. (2017). AVPASS: Leaking and Bypassing Antivirus Detection Model Automatically. 9 indexed citations
14.
Lee, Sangho, et al.. (2017). CAB-Fuzz: Practical Concolic Testing Techniques for COTS Operating Systems.. 689–701. 22 indexed citations
15.
Yun, Insu, Changwoo Min, Xujie Si, et al.. (2016). APISan: Sanitizing {API} Usages through Semantic Cross-Checking. USENIX Security Symposium. 363–378. 36 indexed citations
16.
Song, Chengyu, Hyungon Moon, Monjur Alam, et al.. (2016). HDFI: Hardware-Assisted Data-Flow Isolation. Scholarworks@UNIST (Ulsan National Institute of Science and Technology). 1–17. 86 indexed citations
17.
Jamshed, Muhammad Asim, et al.. (2012). Kargus. 317–328. 115 indexed citations

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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2026