Daniel Plohmann

507 citations
9 papers · 314 · h-index 5

Impact in

Papers in

Daniel Plohmann

6 papers receiving 296 citations

Peers

Daniel Plohmann
Comparison fields: 5 of 19
  • Signal Processing 197
  • Computer Networks and Communications 268
  • Information Systems 133
  • Artificial Intelligence 186
  • Software 5
Replace Amit Praseed with:
Amit Praseed India
Keesook J. Han United States
Changhoon Yoon South Korea
Tianning Zang China
Jeman Park United States
Bong-Nam Noh South Korea
Domhnall Carlin United Kingdom
Maryam Feily Malaysia
Salman Niksefat Iran
Charles Lever United States
Daniel Plohmann relative to Amit Praseed India Amit Praseed's profile →
Citations per field
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Amit Praseed · 1×
Citations per year

Countries citing papers authored by Daniel Plohmann

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Plohmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Daniel Plohmann, 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 Daniel Plohmann Line = papers co-authored together Daniel Plohmann links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
A comprehensive measurement study of domain generating malware
2016113
2 2013106
3 201362
4
Case study of the Miner Botnet
201222
5 201710
6
Patterns of a cooperative malware analysis workflow
20131
7
Malware and Botnet Analysis Methodology.
20120
8 20250
9 20240

About Daniel Plohmann

Daniel Plohmann is a scholar working on Signal Processing, Computer Networks and Communications, Information Systems, Artificial Intelligence and Control and Systems Engineering, having authored 9 papers that have together received 314 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (8 papers), Network Security and Intrusion Detection (6 papers), Digital and Cyber Forensics (3 papers), Peer-to-Peer Network Technologies (2 papers), Forensic Fingerprint Detection Methods (1 paper), Software Engineering Research (1 paper), Software-Defined Networks and 5G (1 paper) and Spam and Phishing Detection (1 paper). The work is most often cited by research in Signal Processing (197 citations), Computer Networks and Communications (268 citations), Information Systems (133 citations), Artificial Intelligence (186 citations) and Software (5 citations). Daniel Plohmann has collaborated with scholars based in Germany and Netherlands. Frequent co-authors include Elmar Gerhards‐Padilla, Herbert Bos, Brett Stone-Gross, Dennis Andriesse, Christian Rossow, Johannes Bader, Michael A. Klatt, Christian Dietrich and Alfred Mahr. Their work appears in journals such as Forensic Science International Digital Investigation, Digital Investigation, Fraunhofer-Publica (Fraunhofer-Gesellschaft), Publication Server of Bonn-Rhein-Sieg University of Applied Sciences (Bonn-Rhein-Sieg University of Applied Sciences) and Figshare.

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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