Yang Xin

114 papers receiving 1.7k citations

Hit Papers

Robust detection for network intrusion of industrial IoT based on multi-CNN fusion 2019 · 243 citations
2432018202620202023200400600

Peers

Yang Xin
Comparison fields: 5 of 137
  • Signal Processing 722
  • Computer Networks and Communications 1.1k
  • Artificial Intelligence 954
  • Information Systems 481
  • Software 69
Replace Junfeng Wang with:
Junfeng Wang China
Farhan Ullah China
Ricard Gavaldà Spain
Vinayakumar Ravi Saudi Arabia
Anca Delia Jurcut Ireland
Hamad Naeem China
Gianni D’Angelo Italy
Fazlullah Khan Pakistan
Changzhen Hu China
Mohammad Alamgir Hossain United Kingdom
Yang Xin relative to Junfeng Wang China Junfeng Wang's profile →
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Junfeng Wang · 1×
Citations per year

Countries citing papers authored by Yang Xin

Since Specialization
Citations

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

Fields of papers citing papers by Yang Xin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine Learning and Deep Learning Methods for Cybersecurity
Hit paper breakdown →
2018737
2
Robust detection for network intrusion of industrial IoT based on multi-CNN fusion
Hit paper breakdown →
2019243
3 201867
4 202055
5 202049
6 201736
7 201231
8 201730
9 202024
10 202122
11 201919
12 202318
13 202117
14 202116
15 202116
16 200916
17 201015
18 202015
19 202014
20 201014

About Yang Xin

Yang Xin is a scholar working on Signal Processing, Computer Networks and Communications, Information Systems, Artificial Intelligence and Software, having authored 128 papers that have together received 1.9k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (35 papers), Cryptography and Data Security (23 papers), Privacy-Preserving Technologies in Data (21 papers), Advanced Malware Detection Techniques (19 papers), Internet Traffic Analysis and Secure E-voting (18 papers), Anomaly Detection Techniques and Applications (14 papers), Cloud Data Security Solutions (12 papers) and Software Engineering Research (8 papers). The work is most often cited by research in Signal Processing (722 citations), Computer Networks and Communications (1.1k citations), Artificial Intelligence (954 citations), Information Systems (481 citations) and Software (69 citations). Yang Xin has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Zhi Liu, Hongliang Zhu, Yuling Chen, Haixia Hou, Yanmiao Li, Chunhua Wang, Yixian Yang, Lizhen Cui, Yuefeng Zhao and Shoushan Luo. Their work appears in journals such as Applied Sciences, IEEE Access, International Journal of Advancements in Computing Technology, Information and Software Technology and Computers & Security.

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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