Purui Su

971 total citations
54 papers, 577 citations indexed

About

Purui Su is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Purui Su has authored 54 papers receiving a total of 577 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Signal Processing, 26 papers in Computer Networks and Communications and 23 papers in Artificial Intelligence. Recurrent topics in Purui Su's work include Advanced Malware Detection Techniques (38 papers), Network Security and Intrusion Detection (19 papers) and Software Testing and Debugging Techniques (18 papers). Purui Su is often cited by papers focused on Advanced Malware Detection Techniques (38 papers), Network Security and Intrusion Detection (19 papers) and Software Testing and Debugging Techniques (18 papers). Purui Su collaborates with scholars based in China, United States and Singapore. Purui Su's co-authors include Dengguo Feng, Wenbo Guo, Gang Wang, Xinyu Xing, Dongliang Mu, Jun Xu, Yanhao Wang, Qi Li, Tiffany Bao and Dinghao Wu and has published in prestigious journals such as IEEE/ACM Transactions on Networking, IEEE Transactions on Visualization and Computer Graphics and IEEE Internet Computing.

In The Last Decade

Purui Su

49 papers receiving 549 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Purui Su China 11 319 286 228 217 160 54 577
Sebastian Schinzel Germany 10 390 1.2× 259 0.9× 158 0.7× 233 1.1× 134 0.8× 24 596
Matthias Neugschwandtner Austria 12 292 0.9× 632 2.2× 377 1.7× 313 1.4× 345 2.2× 21 807
Fredrik Valeur United States 9 335 1.1× 354 1.2× 320 1.4× 197 0.9× 83 0.5× 11 531
Zhaoguo Wang China 10 177 0.6× 411 1.4× 395 1.7× 193 0.9× 199 1.2× 25 612
Tielei Wang China 11 393 1.2× 505 1.8× 153 0.7× 275 1.3× 296 1.9× 17 698
Sangho Lee South Korea 9 196 0.6× 239 0.8× 178 0.8× 288 1.3× 25 0.2× 27 464
Christophe Hauser United States 4 411 1.3× 593 2.1× 180 0.8× 295 1.4× 346 2.2× 13 780
Juraj Somorovsky Germany 16 432 1.4× 244 0.9× 297 1.3× 382 1.8× 119 0.7× 40 735
Lorenzo Martignoni Italy 13 358 1.1× 573 2.0× 280 1.2× 290 1.3× 344 2.1× 17 750
Jonas Zaddach France 5 275 0.9× 411 1.4× 212 0.9× 229 1.1× 143 0.9× 5 555

Countries citing papers authored by Purui Su

Since Specialization
Citations

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

Fields of papers citing papers by Purui Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Purui Su

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

All Works

20 of 20 papers shown
1.
Su, Purui, et al.. (2024). OSmart: Whitebox Program Option Fuzzing. 705–719.
2.
Liu, Yuwei, et al.. (2024). AFGen: Whole-Function Fuzzing for Applications and Libraries. 1901–1919. 2 indexed citations
3.
Wang, Yanhao, et al.. (2024). AirTaint: Making Dynamic Taint Analysis Faster and Easier. 3998–4014. 3 indexed citations
4.
5.
Su, Purui, et al.. (2022). HTFuzz: Heap Operation Sequence Sensitive Fuzzing. 1–13. 5 indexed citations
6.
7.
Cai, Yan, Yutian Tang, Le Yu, et al.. (2020). Resource Race Attacks on Android. 47–58. 6 indexed citations
8.
Cai, Yan, Hong Hu, Purui Su, et al.. (2017). Automatically assessing crashes from heap overflows. 274–279. 7 indexed citations
9.
Su, Purui, et al.. (2017). Towards Efficient Heap Overflow Discovery.. USENIX Security Symposium. 989–1006. 15 indexed citations
10.
Cheng, Yao, et al.. (2016). Attacks and Defence on Android Free Floating Windows. 759–770. 10 indexed citations
11.
Cheng, Yao, et al.. (2014). An Anti-Obfuscation Method for Detecting Similarity Among Android Applications in Large Scale. 51(7). 1446. 3 indexed citations
12.
Li, Qi, Xinwen Zhang, Xin Zhang, & Purui Su. (2014). Invalidating Idealized BGP Security Proposals and Countermeasures. IEEE Transactions on Dependable and Secure Computing. 12(3). 298–311. 10 indexed citations
13.
Cheng, Yao, et al.. (2013). Bind your phone number with caution. 335–340. 14 indexed citations
14.
Liu, Yu, et al.. (2012). Communication Protocol Reverse Engineering of Malware Using Dynamic Taint Analysis. 40(4). 661–668. 1 indexed citations
15.
Yang, Yi, et al.. (2011). Dependency-Based Malware Similarity Comparison Method. Journal of Software. 22(10). 2438–2453. 6 indexed citations
16.
17.
Xu, Jia, Yan Jia, Liang He, Purui Su, & Dengguo Feng. (2010). CloudSEC: A Cloud Architecture for Composing Collaborative Security Services. 47. 703–711. 13 indexed citations
18.
Su, Purui. (2009). Colluding clique detector based on activity similarity in P2P trust model. Journal of Communications. 3 indexed citations
19.
Su, Purui. (2009). P2P-Based Super Botnet:Threats and Defenses. Dianzi xuebao.
20.

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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