Zigang Cao

959 total citations · 1 hit paper
14 papers, 452 citations indexed

About

Zigang Cao is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Zigang Cao has authored 14 papers receiving a total of 452 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 13 papers in Artificial Intelligence and 7 papers in Signal Processing. Recurrent topics in Zigang Cao's work include Network Security and Intrusion Detection (13 papers), Internet Traffic Analysis and Secure E-voting (12 papers) and Advanced Malware Detection Techniques (7 papers). Zigang Cao is often cited by papers focused on Network Security and Intrusion Detection (13 papers), Internet Traffic Analysis and Secure E-voting (12 papers) and Advanced Malware Detection Techniques (7 papers). Zigang Cao collaborates with scholars based in China and Hong Kong. Zigang Cao's co-authors include Gang Xiong, Chang Liu, Longtao He, Zhen Li, Siu‐Ming Yiu, Gaopeng Gou, Cuicui Kang, Min Yang, Junzheng Shi and Zhou Zhao and has published in prestigious journals such as The Journal of Supercomputing.

In The Last Decade

Zigang Cao

14 papers receiving 439 citations

Hit Papers

FS-Net: A Flow Sequence Network For Encrypted Traffic Cla... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zigang Cao China 8 417 383 199 60 48 14 452
Milan Čermák Czechia 8 331 0.8× 344 0.9× 158 0.8× 80 1.3× 51 1.1× 20 392
Petr Velan Czechia 7 284 0.7× 307 0.8× 138 0.7× 54 0.9× 47 1.0× 24 346
Tal Shapira Israel 8 263 0.6× 249 0.7× 91 0.5× 48 0.8× 32 0.7× 10 284
Martin Drašar Czechia 7 273 0.7× 292 0.8× 154 0.8× 60 1.0× 43 0.9× 15 339
Masashi Eto Japan 7 233 0.6× 293 0.8× 178 0.9× 72 1.2× 19 0.4× 19 327
Payap Sirinam United States 3 426 1.0× 293 0.8× 147 0.7× 98 1.6× 95 2.0× 4 445
Thijs van Ede Netherlands 5 211 0.5× 212 0.6× 107 0.5× 58 1.0× 28 0.6× 10 262
Gözde Karataş Türkiye 7 299 0.7× 342 0.9× 215 1.1× 54 0.9× 13 0.3× 12 400
Riccardo Bortolameotti Netherlands 3 198 0.5× 197 0.5× 94 0.5× 55 0.9× 25 0.5× 4 241
Alice Este Italy 7 355 0.9× 361 0.9× 109 0.5× 50 0.8× 28 0.6× 10 384

Countries citing papers authored by Zigang Cao

Since Specialization
Citations

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

Fields of papers citing papers by Zigang Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zigang Cao

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

All Works

14 of 14 papers shown
1.
Liu, Xiaolong, et al.. (2019). Inferring Behaviors via Encrypted Video Surveillance Traffic by Machine Learning. 273–280. 6 indexed citations
2.
Wang, Jibao, Zigang Cao, Cuicui Kang, & Gang Xiong. (2019). User Behavior Classification in Encrypted Cloud Camera Traffic. 1–6. 9 indexed citations
3.
Guo, Yu, Junzheng Shi, Zigang Cao, et al.. (2019). Machine Learning Based CloudBot Detection Using Multi-Layer Traffic Statistics. 2428–2435. 10 indexed citations
4.
Liu, Chang, Longtao He, Gang Xiong, Zigang Cao, & Zhen Li. (2019). FS-Net: A Flow Sequence Network For Encrypted Traffic Classification. 1171–1179. 269 indexed citations breakdown →
5.
Liu, Chang, Zigang Cao, Zhen Li, & Gang Xiong. (2018). LaFFT: Length-Aware FFT Based Fingerprinting for Encrypted Network Traffic Classification. 1. 1–6. 8 indexed citations
6.
Liu, Chang, Zigang Cao, Gang Xiong, et al.. (2018). MaMPF: Encrypted Traffic Classification Based on Multi-Attribute Markov Probability Fingerprints. 1–10. 62 indexed citations
7.
Shi, Junzheng, et al.. (2018). Classifying User Activities in the Encrypted WeChat Traffic. 1–8. 11 indexed citations
8.
Zhen, Li, et al.. (2018). SSL/TLS Security Exploration Through X.509 Certificate’s Life Cycle Measurement. 652–655. 4 indexed citations
9.
Cao, Zigang, et al.. (2018). Machine Learning Based DDos Detection Through NetFlow Analysis. 1–6. 31 indexed citations
10.
Yang, Min, et al.. (2017). Personalized Response Generation via Domain adaptation. 1021–1024. 27 indexed citations
11.
12.
Zhang, Ziqing, et al.. (2017). Metric learning with statistical features for network traffic classification. 1–7. 3 indexed citations
13.
Li, Zhen, et al.. (2016). A network attack forensic platform against HTTP evasive behavior. The Journal of Supercomputing. 73(7). 3053–3064. 7 indexed citations
14.
Cao, Zigang, Gang Xiong, & Li Guo. (2015). MimicHunter: A General Passive Network Protocol Mimicry Detection Framework. 1. 271–278. 2 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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