Paul D. Yoo

3.6k citations
84 papers · 2.4k indexed · 1 hit paper · h-index 26
Topics
Network Security and Intrusion Detection (17 papers)Machine Learning in Bioinformatics (15 papers)Advanced Malware Detection Techniques (12 papers)

In The Last Decade

Paul D. Yoo

82 papers receiving 2.3k citations

Hit Papers

Efficient Machine Learning for Big Data: A Review20152026201820222015100200300400

Peers

Paul D. Yoo
Comparison fields: 5 of 157
  • Computer Networks and Communications 880
  • Artificial Intelligence 879
  • Electrical and Electronic Engineering 495
  • Signal Processing 448
  • Information Systems 336
Replace Crina Groşan with:
Crina Groşan Romania
Yuehui Chen China
Xiaochun Cheng United Kingdom
Maryam M. Najafabadi United States
Kalyan Veeramachaneni United States
Ala’ M. Al-Zoubi Jordan
Christian Esposito Italy
Aiiad Albeshri Saudi Arabia
Mohiuddin Ahmed Australia
Alberto Cano United States
Paul D. Yoo relative to Crina Groşan Romania Crina Groşan's profile →
Citations per field
00.5×1.5×2.2×
Crina Groşan · 1×
Citations per year

Countries citing papers authored by Paul D. Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Paul D. Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul D. Yoo. 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 Paul D. Yoo. The network helps show where Paul D. Yoo may publish in the future.

Co-authorship network of co-authors of Paul D. Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Paul D. Yoo. A scholar is included among the top collaborators of Paul D. Yoo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul D. Yoo. Paul D. Yoo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 20
2 5
3 5
4 17
5 33
6 35
7 79
8 18
9 47
10 60
11 150
12 5
13
Semi-supervised Botnet Detection Using Ant Colony Clustering
8
14
Simulated Attack on DNP3 Protocol in SCADA System
15
15 3
16 10
17 6
18 24
19 51
20 22

About Paul D. Yoo

Paul D. Yoo is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 84 papers that have together received 2.4k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (17 papers), Machine Learning in Bioinformatics (15 papers) and Advanced Malware Detection Techniques (12 papers). The work is most often cited by research in Signal Processing (448 citations), Computer Networks and Communications (880 citations) and Artificial Intelligence (879 citations). Paul D. Yoo has collaborated with scholars based in United Arab Emirates, United Kingdom and Australia. Frequent co-authors include Kamal Taha, Sami Muhaidat, Omar Y. Al-Jarrah, George K. Karagiannidis, Yousof Al-Hammadi, Chan Yeob Yeun, Kwangjo Kim, Albert Y. Zomaya, Bing Bing Zhou and Vasilios Katos. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Communications Surveys & Tutorials.

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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