Beibei Li

3.1k citations
157 papers · 2.3k · 1 hit paper · h-index 26

Impact in

Papers in

Beibei Li

131 papers receiving 2.2k citations

Beibei Li's Hit Papers

DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems 2020 · 452 citations
4520+2+4Years since publication100200300400

Peers

Beibei Li
Comparison fields: 5 of 141
  • Computer Networks and Communications 968
  • Control and Systems Engineering 727
  • Signal Processing 326
  • Artificial Intelligence 914
  • Information Systems 338
Replace Xiaofeng Liao with:
Xiaofeng Liao China
Fengjun Li United States
Giuseppe Lo Re Italy
Fawaz Alsolami Saudi Arabia
Dezhi Han China
Hongxiang Li China
Peiying Zhang China
Qing Yang United States
Mehdi Gheisari China
Azana Hafizah Mohd Aman Malaysia
Beibei Li relative to Xiaofeng Liao China Xiaofeng Liao's profile →
Citations per field
00.5×2.7×
Xiaofeng Liao · 1×
Citations per year

Countries citing papers authored by Beibei Li

Since Specialization
Citations

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

Fields of papers citing papers by Beibei Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 157 papers — load more, or switch the sort, to bring in the rest.

#Work
1
DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems
Hit paper breakdown →
2020452
2 2019153
3 2020123
4 2016109
5 202179
6 201875
7 201672
8 201564
9 202253
10 200745
11 202244
12 201542
13 202034
14 201333
15 202133
16 202131
17 201929
18 202129
19 202229
20 202229

About Beibei Li

Beibei Li is a scholar working on Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering and Information Systems, having authored 157 papers that have together received 2.3k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (31 papers), Smart Grid Security and Resilience (27 papers), Privacy-Preserving Technologies in Data (16 papers), Advanced Malware Detection Techniques (16 papers), Cryptography and Data Security (14 papers), Internet Traffic Analysis and Secure E-voting (13 papers), Anomaly Detection Techniques and Applications (10 papers) and Blockchain Technology Applications and Security (9 papers). The work is most often cited by research in Computer Networks and Communications (968 citations), Control and Systems Engineering (727 citations), Signal Processing (326 citations), Artificial Intelligence (914 citations) and Information Systems (338 citations). Beibei Li has collaborated with scholars based in China, Singapore and Canada. Frequent co-authors include Rongxing Lu, Tao Li, Gaoxi Xiao, Yuhao Wu, Jiarui Song, Liang Zhao, Kim‐Kwang Raymond Choo, Haiyong Bao, Wei Wang and Ruilong Deng. Their work appears in journals such as IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, Future Generation Computer Systems, Computers & Security and IEEE Transactions on Information Forensics and 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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