Thomas E. Daniels

588 citations
24 papers · 354 · h-index 11

Impact in

Papers in

Thomas E. Daniels

22 papers receiving 308 citations

Peers

Thomas E. Daniels
Comparison fields: 5 of 36
  • Signal Processing 178
  • Computer Networks and Communications 215
  • Hardware and Architecture 46
  • Information Systems 134
  • Artificial Intelligence 177
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D. Morató Spain
Jeong‐Nyeo Kim South Korea
Claudio Marforio Switzerland
Eduardo Magaña Spain
Mikel Izal Spain
Nouha Oualha France
Gaopeng Jian China
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Citations per field
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Citations per year

Countries citing papers authored by Thomas E. Daniels

Since Specialization
Citations

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

Fields of papers citing papers by Thomas E. Daniels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas E. Daniels. 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 Thomas E. Daniels. The network helps show where Thomas E. Daniels may publish in the future.

Co-authors

The 13 scholars most cited alongside Thomas E. Daniels, 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 Thomas E. Daniels Line = papers co-authored together Thomas E. Daniels links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Device Identification via Analog Signal Fingerprinting: A Matched Filter Approach
200673
2 200853
3 201230
4 199925
5 200624
6 200921
7 200520
8 200519
9 200914
10
Network Forensics Analysis with Evidence Graphs.
200510
11 200610
12 20039
13 19718
14
Reference Models for the Concealment and Observation of Origin Identity in Store-and-Forward Networks
20027
15 20097
16 20015
17 20024
18 20094
19 20063
20 20093

About Thomas E. Daniels

Thomas E. Daniels is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Signal Processing and Hardware and Architecture, having authored 24 papers that have together received 354 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (15 papers), Internet Traffic Analysis and Secure E-voting (10 papers), Advanced Malware Detection Techniques (7 papers), Digital and Cyber Forensics (4 papers), Network Packet Processing and Optimization (3 papers), Spam and Phishing Detection (3 papers), Complex Network Analysis Techniques (3 papers) and Digital Media Forensic Detection (2 papers). The work is most often cited by research in Signal Processing (178 citations), Computer Networks and Communications (215 citations), Hardware and Architecture (46 citations), Information Systems (134 citations) and Artificial Intelligence (177 citations). Thomas E. Daniels has collaborated with scholars based in United States. Frequent co-authors include Wei Wang, Ryan Gerdes, Mani Mina, Eugene H. Spafford, Chang Su, Wei Wang, Basheer Al‐Duwairi, Wei Wang, Benjamin Anderson and Chang Su. Their work appears in journals such as American Quarterly, IEEE Transactions on Information Forensics and Security, Journal of Computer Security, ACM Transactions on Information and System Security and Purdue e-Pubs (Purdue University System).

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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