Thomas Hupperich

628 citations
22 papers · 359 · h-index 10

Impact in

Papers in

Thomas Hupperich

20 papers receiving 338 citations

Peers

Thomas Hupperich
Comparison fields: 5 of 37
  • Signal Processing 120
  • Computer Networks and Communications 239
  • Artificial Intelligence 213
  • Information Systems 140
  • Human-Computer Interaction 22
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Xianghang Mi United States
Antonis Papadogiannakis Greece
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Akira Yamada Japan
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Tobias Pulls Sweden
Tomasz Bujlow Denmark
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Mark O'Neill United States
Cristian Hesselman Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Thomas Hupperich

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Hupperich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Exit from hell? reducing the impact of amplification DDoS attacks
2014115
2 201561
3
Hell of a handshake: abusing TCP for reflective amplification DDoS attacks
201432
4 201530
5
Use the force: Evaluating force-sensitive authentication for mobile devices
201624
6 201224
7 202118
8 201812
9 201711
10 202110
11 20224
12 20234
13 20243
14 20233
15 20202
16 20232
17 20221
18 20231
19 20201
20 20201

About Thomas Hupperich

Thomas Hupperich is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Signal Processing and Sociology and Political Science, having authored 22 papers that have together received 359 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (6 papers), User Authentication and Security Systems (6 papers), Opportunistic and Delay-Tolerant Networks (5 papers), Network Security and Intrusion Detection (5 papers), Internet Traffic Analysis and Secure E-voting (5 papers), Mobile Ad Hoc Networks (5 papers), Privacy, Security, and Data Protection (4 papers) and Caching and Content Delivery (3 papers). The work is most often cited by research in Signal Processing (120 citations), Computer Networks and Communications (239 citations), Artificial Intelligence (213 citations), Information Systems (140 citations) and Human-Computer Interaction (22 citations). Thomas Hupperich has collaborated with scholars based in Germany, Netherlands and Australia. Frequent co-authors include Thorsten Holz, Marc Kührer, Christian Rossow, Katharina Krombholz, Marcel Winandy, Giorgio Giacinto, Ahmad‐Reza Sadeghi, Davide Maiorca, Hans Löhr and Anna Förster. Their work appears in journals such as Journal of Sensor and Actuator Networks, IEEE Internet Computing, Blockchain Research and Applications, Computers & Security and Forensic Science International Digital Investigation.

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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