Tamas Abraham

546 citations
14 papers · 274 · h-index 6

Impact in

Papers in

    • Adversarial Robustness in Machine Learning 8
    • Anomaly Detection Techniques and Applications 4
    • Advanced Malware Detection Techniques 6
    • Data Management and Algorithms 2

Tamas Abraham

12 papers receiving 215 citations

Peers

Tamas Abraham
Comparison fields: 5 of 47
  • Signal Processing 167
  • Geography, Planning and Development 69
  • Computer Networks and Communications 140
  • Information Systems 92
  • Artificial Intelligence 115
Replace Philippe Rigaux with:
Philippe Rigaux France
Ahmed R. Mahmood United States
Udo W. Lipeck Germany
Sukho Lee South Korea
Ahmed M. Aly United States
Jesús M. Almendros-Jiménez Spain
Hans-Werner Six Germany
Darius Šidlauskas Denmark
Bruno Becker Germany
Erik Hoel United States
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Citations per field
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Citations per year

Countries citing papers authored by Tamas Abraham

Since Specialization
Citations

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

Fields of papers citing papers by Tamas Abraham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Tamas Abraham, 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 Tamas Abraham Line = papers co-authored together Tamas Abraham links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 1999128
2
IDDM: Intrusion Detection Using Data Mining Techniques
200143
3 200336
4 201817
5 199817
6
Event sequence mining to develop profiles for computer forensic investigation purposes
200616
7 20215
8 20234
9 20204
10
Investigative Profile Analysis With Computer Forensic Log Data Using Attribute Generalisation.
20022
11
Adversarial Reinforcement Learning under Partial Observability in Software-Defined Networking.
20191
12 20241
13 20250
14 20210

About Tamas Abraham

Tamas Abraham is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Information Systems and Molecular Biology, having authored 14 papers that have together received 274 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (8 papers), Advanced Malware Detection Techniques (6 papers), Anomaly Detection Techniques and Applications (4 papers), Digital and Cyber Forensics (3 papers), Network Security and Intrusion Detection (3 papers), Advanced Database Systems and Queries (2 papers), Data Mining Algorithms and Applications (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Signal Processing (167 citations), Geography, Planning and Development (69 citations), Computer Networks and Communications (140 citations), Information Systems (92 citations) and Artificial Intelligence (115 citations). Tamas Abraham has collaborated with scholars based in Australia and India. Frequent co-authors include John F. Roddick, Olivier De Vel, Paul Montague, Christopher Leckie, Sarah Erfani, Benjamin I. P. Rubinstein, Yi Han, Tansu Alpcan, Trung Le and Dinh Phung. Their work appears in journals such as GeoInformatica, World Wide Web, AJIS. Australasian journal of information systems/AJIS. Australian journal of information systems/Australian journal of information systems, Lecture notes in computer science and Proceedings of the AAAI Conference on Artificial Intelligence.

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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