Xiangyun Tang

993 citations
28 papers · 649 indexed · 1 hit paper · h-index 11
Topics
Privacy-Preserving Technologies in Data (10 papers)Network Security and Intrusion Detection (7 papers)Cryptography and Data Security (7 papers)

In The Last Decade

Xiangyun Tang

19 papers receiving 634 citations

Hit Papers

Privacy-Preserving Support Vector Machine Training Over B...20192026202120232019100200300

Peers

Xiangyun Tang
Comparison fields: 5 of 61
  • Artificial Intelligence 346
  • Information Systems 322
  • Computer Networks and Communications 290
  • Electrical and Electronic Engineering 79
  • Computer Vision and Pattern Recognition 57
Replace Mikail Mohammed Salim with:
Mikail Mohammed Salim South Korea
Liang Xue Canada
Vijey Thayananthan Saudi Arabia
Carsten Rudolph Australia
MingJian Tang Australia
Aaisha Makkar India
Weichao Gao United States
Songyou Xie China
Mosleh M. Abualhaj Jordan
Xiangyun Tang relative to Mikail Mohammed Salim South Korea Mikail Mohammed Salim's profile →
Citations per field
00.5×6.6×
Mikail Mohammed Salim · 1×
Citations per year

Countries citing papers authored by Xiangyun Tang

Since Specialization
Citations

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

Fields of papers citing papers by Xiangyun Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangyun Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangyun Tang. A scholar is included among the top collaborators of Xiangyun Tang 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 Xiangyun Tang. Xiangyun Tang 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
#WorkIndexed citations
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2 1
3 0
4 0
5 0
6 10
7 1
8 1
9 0
10 4
11 1
12 0
13 14
14 1
15 1
16 4
17 41
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19 16
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Privacy-Preserving Support Vector Machine Training Over Blockchain-Based Encrypted IoT Data in Smart Citiesbreakdown →
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About Xiangyun Tang

Xiangyun Tang is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 28 papers that have together received 649 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (10 papers), Network Security and Intrusion Detection (7 papers) and Cryptography and Data Security (7 papers). The work is most often cited by research in Information Systems (322 citations), Computer Networks and Communications (290 citations) and Artificial Intelligence (346 citations). Xiangyun Tang has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Liehuang Zhu, Meng Shen, Xiaojiang Du, Mohsen Guizani, Jie Zhang, Ke Xu, Dusit Niyato, Jiawen Kang, Qi Li and Qiang Qu. Their work appears in journals such as IEEE Journal on Selected Areas in Communications, IEEE Transactions on Vehicular Technology and IEEE Internet of Things Journal.

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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