Beibei Li

3.1k citations
142 papers · 2.2k indexed · 1 hit paper · h-index 25

Impact in

Papers in

Beibei Li

120 papers receiving 2.1k citations

Hit Papers

DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems 2020 · 410 citations
4102020202620222024100200300400

Peers

Beibei Li
Comparison fields: 5 of 138
  • Computer Networks and Communications 921
  • Control and Systems Engineering 692
  • Signal Processing 299
  • Artificial Intelligence 869
  • Information Systems 311
Replace Jun Peng with:
Jun Peng China
Kim Fung Tsang Hong Kong
Fawaz Alsolami Saudi Arabia
Xiaofeng Liao China
Weiping Wang China
Peiying Zhang China
Rosilah Hassan Malaysia
Tole Sutikno Indonesia
Beibei Li relative to Jun Peng China Jun Peng's profile →
Citations per field
00.5×3.6×
Jun Peng · 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-authorship network

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
#Work
1 20252
2 20242
3 20242
4 20246
5 20243
6 20242
7 20242
8 20241
9 202311
10 20232
11 20232
12 202310
13 20239
14 202225
15 202230
16 20214
17 202171
18 202031
19 20197
20 2019148

About Beibei Li

Beibei Li is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Control and Systems Engineering and Information Systems, having authored 142 papers that have together received 2.2k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (28 papers), Smart Grid Security and Resilience (24 papers), Privacy-Preserving Technologies in Data (15 papers), Cryptography and Data Security (14 papers), Advanced Malware Detection Techniques (13 papers), Internet Traffic Analysis and Secure E-voting (12 papers), Anomaly Detection Techniques and Applications (11 papers) and Blockchain Technology Applications and Security (9 papers). The work is most often cited by research in Computer Networks and Communications (921 citations), Control and Systems Engineering (692 citations), Signal Processing (299 citations), Artificial Intelligence (869 citations) and Information Systems (311 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, Ruilong Deng and Wei Wang. Their work appears in journals such as IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, Future Generation Computer Systems, Applied Soft Computing 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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