Lifa Wu

554 citations
27 papers · 378 · 1 hit paper · h-index 7

Impact in

Papers in

Lifa Wu

26 papers receiving 359 citations

Lifa Wu's Hit Papers

Building Auto-Encoder Intrusion Detection System based on random forest feature selection 2020 · 240 citations
2400+2+4Years since publication50100150200

Peers

Lifa Wu
Comparison fields: 5 of 63
  • Signal Processing 128
  • Computer Networks and Communications 241
  • Artificial Intelligence 245
  • Software 18
  • Information Systems 56
Replace Tianlong Yu with:
Tianlong Yu United States
Phu H. Phung United States
Kai Cheng China
Yubo Song China
Chaochao Luo China
Firdaus Afifi Malaysia
Anni Peng China
Abdullah Alzaqebah Jordan
Ali Alqazzaz Saudi Arabia
Kehe Wu China
Lifa Wu relative to Tianlong Yu United States Tianlong Yu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Lifa Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lifa Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Lifa Wu, 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 Lifa Wu Line = papers co-authored together Lifa Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Building Auto-Encoder Intrusion Detection System based on random forest feature selection
Hit paper breakdown →
2020240
2 201920
3 202318
4 202311
5 202010
6 20219
7 20237
8
Double Reversible Watermarking Algorithm for Image Tamper Detection.
20166
9 20216
10 20135
11 20215
12 20234
13 20244
14 20174
15 20194
16 20194
17 20243
18 20233
19 20173
20 20203

About Lifa Wu

Lifa Wu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Software and Information Systems, having authored 27 papers that have together received 378 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (8 papers), Network Security and Intrusion Detection (8 papers), Software Testing and Debugging Techniques (7 papers), Internet Traffic Analysis and Secure E-voting (7 papers), Anomaly Detection Techniques and Applications (5 papers), Software Reliability and Analysis Research (3 papers), Advanced Steganography and Watermarking Techniques (3 papers) and Security and Verification in Computing (3 papers). The work is most often cited by research in Signal Processing (128 citations), Computer Networks and Communications (241 citations), Artificial Intelligence (245 citations), Software (18 citations) and Information Systems (56 citations). Lifa Wu has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include Wei Chen, Qianru Zhang, Yihao Li, Yuxiao Liu, Hong Zheng, He Sun, Qi Li, Feng Zhu, Min Chen and Fu Xiao. Their work appears in journals such as Computers & Security, IEEE Access, Journal of Information Security and Applications, China Communications 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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