Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Toward Automated Dynamic Malware Analysis Using CWSandbox
Countries citing papers authored by Carsten Willems
Since
Specialization
Citations
This map shows the geographic impact of Carsten Willems'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 Carsten Willems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carsten Willems more than expected).
This network shows the impact of papers produced by Carsten Willems. 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 Carsten Willems. The network helps show where Carsten Willems may publish in the future.
Co-authorship network of co-authors of Carsten Willems
This figure shows the co-authorship network connecting the top 25 collaborators of Carsten Willems.
A scholar is included among the top collaborators of Carsten Willems based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Carsten Willems. Carsten Willems is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Dewald, Andreas, et al.. (2011). Analyse und Vergleich von BckR2D2-I und II. OPUS FAU (Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV), on behalf of the Universitätsbibliothek Erlangen-Nürnberg). 47–58.2 indexed citations
8.
Willems, Carsten. (2011). Internals of Windows Memory Management (not only) for Malware Analysis. MADOC (University of Mannheim).1 indexed citations
9.
Rieck, Konrad, Philipp Trinius, Carsten Willems, & Thorsten Holz. (2011). Automatic analysis of malware behavior using machine learning. Journal of Computer Security. 19(4). 639–668.435 indexed citations breakdown →
10.
Freiling, Felix, Jan Göbel, Thorsten Holz, et al.. (2010). The InMAS Approach. Technische Universität Dortmund Eldorado (Technische Universität Dortmund).5 indexed citations
11.
Trinius, Philipp, Carsten Willems, Thorsten Holz, & Konrad Rieck. (2009). A malware instruction set for behavior-based analysis. MADOC (University of Mannheim). 205–216.43 indexed citations
Willems, Carsten, et al.. (1995). Concepts of GTDs: an oncology workstation.. PubMed. 8 Pt 1. 759–62.5 indexed citations
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.