Kuo-Ping Wu

976 citations
18 papers · 774 · 1 hit paper · h-index 8

Impact in

Papers in

Kuo-Ping Wu

17 papers receiving 734 citations

Kuo-Ping Wu's Hit Papers

DroidMat: Android Malware Detection through Manifest and API Calls Tracing 2012 · 495 citations
4950+4+9Years since publication100200300400

Peers

Kuo-Ping Wu
Comparison fields: 5 of 83
  • Software 305
  • Signal Processing 556
  • Computer Networks and Communications 433
  • Information Systems 257
  • Artificial Intelligence 140
Replace Guangquan Xu with:
Guangquan Xu China
Saihua Cai China
Cornel Barna Canada
R. Frank United Kingdom
Zhiqiang Wang China
Christopher M. Poskitt Singapore
Quoc-Dung Ngo Vietnam
Lina Gong China
Kuo-Ping Wu relative to Guangquan Xu China Guangquan Xu's profile →
Citations per field
00.5×5×10×14.4×
Guangquan Xu · 1×
Citations per year

Countries citing papers authored by Kuo-Ping Wu

Since Specialization
Citations

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

Fields of papers citing papers by Kuo-Ping Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Kuo-Ping 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 Kuo-Ping Wu Line = papers co-authored together Kuo-Ping Wu links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1
DroidMat: Android Malware Detection through Manifest and API Calls Tracing
Hit paper breakdown →
2012495
2 2008174
3 201414
4 201314
5 200613
6 201212
7 200210
8 20129
9 20137
10
Obfuscated malicious JavaScript detection by Causal Relations Finding
20117
11 20124
12 20153
13 20053
14 20153
15 20162
16 20062
17 20061
18 20111

About Kuo-Ping Wu

Kuo-Ping Wu is a scholar working on Signal Processing, Information Systems, Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering, having authored 18 papers that have together received 774 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (6 papers), Spam and Phishing Detection (5 papers), Face and Expression Recognition (5 papers), Advanced Algorithms and Applications (5 papers), Network Security and Intrusion Detection (4 papers), Neural Networks and Applications (3 papers), Internet Traffic Analysis and Secure E-voting (3 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Software (305 citations), Signal Processing (556 citations), Computer Networks and Communications (433 citations), Information Systems (257 citations) and Artificial Intelligence (140 citations). Kuo-Ping Wu has collaborated with scholars based in Taiwan, Jordan and United States. Frequent co-authors include Te-En Wei, Ching-Hao Mao, Hahn-Ming Lee, Sheng‐De Wang, Albert B. Jeng, Ismail Al-Taharwa, Shyi‐Ming Chen, Shin‐Ming Cheng, Christos Faloutsos and Jason C.H. Shih. Their work appears in journals such as Pattern Recognition, Lecture notes in computer science, Journal of information science and engineering, Communications in computer and information science and NTUR (臺灣機構典藏).

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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