Daniel Gibert
Impact in
- Signal Processing top 1%
- Advanced Malware Detection Techniques
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- Network Security and Intrusion Detection
Papers in
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- Advanced Malware Detection Techniques 13
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- Anomaly Detection Techniques and Applications 8
- Adversarial Robustness in Machine Learning 3
- Co-authors
- Jordi Planes (12 shared papers)Carles Mateu (9 shared papers)Quan Le (5 shared papers)João Marques‐Silva (1 shared paper)Matt Fredrikson (1 shared paper)Alicia Crespo (1 shared paper)Álvaro de Gracia (1 shared paper)Cèsar Fernández (1 shared paper)
In The Last Decade
Daniel Gibert
16 papers receiving 817 citations
Daniel Gibert's Hit Papers
Peers
Comparison fields: 5 of 60
- Signal Processing 723
- Computer Networks and Communications 611
- Software 76
- Artificial Intelligence 422
- Information Systems 281
Countries citing papers authored by Daniel Gibert
This map shows the geographic impact of Daniel Gibert'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 Gibert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gibert more than expected).
Fields of papers citing papers by Daniel Gibert
This network shows the impact of papers produced by Daniel Gibert. 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 Gibert. The network helps show where Daniel Gibert may publish in the future.
Co-authors
The 12 scholars most cited alongside Daniel Gibert, 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 | The rise of machine learning for detection and classification of malware: Research developments, trends and challenges Hit paper breakdown → | 2020 | 372 |
| 2 | 2018 | 182 | |
| 3 | 2020 | 94 | |
| 4 | 2018 | 56 | |
| 5 | 2022 | 49 | |
| 6 | 2019 | 29 | |
| 7 | 2020 | 17 | |
| 8 | 2021 | 13 | |
| 9 | 2020 | 12 | |
| 10 | 2023 | 10 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2022 | 1 | |
| 16 | 1981 | 1 | |
| 17 | 2025 | 0 |
About Daniel Gibert
Daniel Gibert is a scholar working on Signal Processing, Artificial Intelligence, Computer Networks and Communications, Information Systems and History and Philosophy of Science, having authored 17 papers that have together received 851 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (13 papers), Anomaly Detection Techniques and Applications (8 papers), Network Security and Intrusion Detection (8 papers), Adversarial Robustness in Machine Learning (3 papers), Software Engineering Research (2 papers), Spam and Phishing Detection (1 paper), Ancient and Medieval Archaeology Studies (1 paper) and Historical Studies and Socio-cultural Analysis (1 paper). The work is most often cited by research in Signal Processing (723 citations), Computer Networks and Communications (611 citations), Software (76 citations), Artificial Intelligence (422 citations) and Information Systems (281 citations). Daniel Gibert has collaborated with scholars based in Spain, Ireland and Greece. Frequent co-authors include Jordi Planes, Carles Mateu, Quan Le, João Marques‐Silva, Matt Fredrikson, Alicia Crespo, Álvaro de Gracia, Cèsar Fernández, Josep Argelich and Teresa Alsinet. Their work appears in journals such as Computers & Security, Expert Systems with Applications, Journal of Network and Computer Applications, Applied Thermal Engineering and International Journal of Computational Intelligence Systems.
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.