Frederick T. Sheldon

2.9k citations
165 papers · 1.9k · 1 hit paper · h-index 22

Impact in

Papers in

Frederick T. Sheldon

152 papers receiving 1.8k citations

Frederick T. Sheldon's Hit Papers

IoT Intrusion Detection Using Machine Learning with a Novel High Performing Feature Selection Method 2022 · 128 citations
1280+1+2Years since publication4080120

Peers

Frederick T. Sheldon
Comparison fields: 5 of 89
  • Signal Processing 516
  • Computer Networks and Communications 1.1k
  • Information Systems 859
  • Software 147
  • Artificial Intelligence 706
Replace Khaled M. Khan with:
Khaled M. Khan Qatar
Igor Nai Fovino Italy
Peter Mell United States
Sandro Etalle Netherlands
Thomas A. Longstaff United States
Sajjan G. Shiva United States
Joaquín García-Alfaro France
Sven Hartmann Germany
Xiaohong Li China
Zhenyu Wu China
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Citations per field
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Citations per year

Countries citing papers authored by Frederick T. Sheldon

Since Specialization
Citations

This map shows the geographic impact of Frederick T. Sheldon'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 Frederick T. Sheldon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frederick T. Sheldon more than expected).

Fields of papers citing papers by Frederick T. Sheldon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frederick T. Sheldon. 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 Frederick T. Sheldon. The network helps show where Frederick T. Sheldon may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 165 papers — load more, or switch the sort, to bring in the rest.

#Work
1
IoT Intrusion Detection Using Machine Learning with a Novel High Performing Feature Selection Method
Hit paper breakdown →
2022128
2 2017120
3 202094
4 202279
5 202177
6 202167
7 200258
8 201048
9 201848
10 201936
11 202036
12 200734
13 202133
14 202030
15 202329
16 199229
17 201228
18 201626
19 201723
20 201323

About Frederick T. Sheldon

Frederick T. Sheldon is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Signal Processing and Control and Systems Engineering, having authored 165 papers that have together received 1.9k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (55 papers), Information and Cyber Security (35 papers), Advanced Malware Detection Techniques (33 papers), Smart Grid Security and Resilience (30 papers), Software Reliability and Analysis Research (24 papers), Software Engineering Research (12 papers), Security and Verification in Computing (12 papers) and Formal Methods in Verification (11 papers). The work is most often cited by research in Signal Processing (516 citations), Computer Networks and Communications (1.1k citations), Information Systems (859 citations), Software (147 citations) and Artificial Intelligence (706 citations). Frederick T. Sheldon has collaborated with scholars based in United States, Saudi Arabia and Tunisia. Frequent co-authors include Robert K. Abercrombie, Ananth A. Jillepalli, Mohammad Ashrafuzzaman, Sajjan G. Shiva, Saikat Das, Ali Mili, Daniel Conte de Leon, Abdullah Alqahtani, Yacine Chakhchoukh and Michael Haney. Their work appears in journals such as Sensors, Future Internet, IEEE Access, IEEE Security & Privacy and Applied Sciences.

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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