Tim Booij
Impact in
- Signal Processing top 5%
- Advanced Malware Detection Techniques
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- Network Security and Intrusion Detection
Papers in
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- Network Security and Intrusion Detection 4
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- Spam and Phishing Detection 3
- Cybercrime and Law Enforcement Studies 2
- Co-authors
- Irina Chiscop (1 shared paper)Erik Meeuwissen (1 shared paper)Nour Moustafa (1 shared paper)Frank den Hartog (1 shared paper)Christian Doerr (2 shared papers)Andrea Continella (1 shared paper)Thijs van Ede (1 shared paper)Luca Allodi (1 shared paper)
- Journals
- IEEE Internet of Things Journal (1 paper)Research Repository (Delft University of Technology) (2 papers)TNO Repository (1 paper)TU/e Research Portal (1 paper)
- Partner nations
- NetherlandsCanadaAustralia
In The Last Decade
Tim Booij
6 papers receiving 300 citations
Tim Booij's Hit Papers
Peers
Comparison fields: 5 of 31
- Signal Processing 146
- Computer Networks and Communications 244
- Artificial Intelligence 187
- Information Systems 58
- Control and Systems Engineering 35
Countries citing papers authored by Tim Booij
This map shows the geographic impact of Tim Booij'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 Tim Booij with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Booij more than expected).
Fields of papers citing papers by Tim Booij
This network shows the impact of papers produced by Tim Booij. 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 Tim Booij. The network helps show where Tim Booij may publish in the future.
Co-authors
The 9 scholars most cited alongside Tim Booij, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | ToN_IoT: The Role of Heterogeneity and the Need for Standardization of Features and Attack Types in IoT Network Intrusion Data Sets Hit paper breakdown → | 2021 | 251 |
| 2 | 2019 | 21 | |
| 3 | Inadvertently Making Cyber Criminals Rich: A Comprehensive Study of Cryptojacking Campaigns at Internet Scale | 2019 | 16 |
| 4 | 2022 | 11 | |
| 5 | Catching Phishers By Their Bait: Investigating the Dutch Phishing Landscape through Phishing Kit Detection | 2021 | 6 |
| 6 | 2021 | 6 |
About Tim Booij
Tim Booij is a scholar working on Computer Networks and Communications, Information Systems, Signal Processing, Artificial Intelligence and Strategy and Management, having authored 6 papers that have together received 311 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (4 papers), Network Security and Intrusion Detection (4 papers), Spam and Phishing Detection (3 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Cybercrime and Law Enforcement Studies (2 papers), Imbalanced Data Classification Techniques (1 paper), Crime, Illicit Activities, and Governance (1 paper) and Franchising Strategies and Performance (1 paper). The work is most often cited by research in Signal Processing (146 citations), Computer Networks and Communications (244 citations), Artificial Intelligence (187 citations), Information Systems (58 citations) and Control and Systems Engineering (35 citations). Tim Booij has collaborated with scholars based in Netherlands, Canada and Australia. Frequent co-authors include Irina Chiscop, Erik Meeuwissen, Nour Moustafa, Frank den Hartog, Christian Doerr, Andrea Continella, Thijs van Ede, Luca Allodi and Savio Sciancalepore. Their work appears in journals such as IEEE Internet of Things Journal, Research Repository (Delft University of Technology), TNO Repository and TU/e Research Portal.
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.