Kim Wuyts

1.3k total citations · 1 hit paper
28 papers, 748 citations indexed

About

Kim Wuyts is a scholar working on Information Systems, Sociology and Political Science and Signal Processing. According to data from OpenAlex, Kim Wuyts has authored 28 papers receiving a total of 748 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Information Systems, 14 papers in Sociology and Political Science and 14 papers in Signal Processing. Recurrent topics in Kim Wuyts's work include Privacy, Security, and Data Protection (14 papers), Advanced Malware Detection Techniques (14 papers) and Information and Cyber Security (10 papers). Kim Wuyts is often cited by papers focused on Privacy, Security, and Data Protection (14 papers), Advanced Malware Detection Techniques (14 papers) and Information and Cyber Security (10 papers). Kim Wuyts collaborates with scholars based in Belgium, Netherlands and Germany. Kim Wuyts's co-authors include Wouter Joosen, Riccardo Scandariato, Bart Preneel, Mina Deng, Laurens Sion, Dimitri Van Landuyt, Nadine Possemiers, Peggy Valcke, Viviane M. Conraads and Emeline M. Van Craenenbroeck and has published in prestigious journals such as European Heart Journal, Journal of Systems and Software and Computers & Security.

In The Last Decade

Kim Wuyts

26 papers receiving 724 citations

Hit Papers

align trajectories

What are hit papers?

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.

A privacy threat analysis framework: supporting the elicitation and fulfillment of privacy requirements

2010 308 citations Mina Deng, Kim Wuyts et al. Requirements Engineering profile →

Peers

Kim Wuyts

IS

SPS

AI

SP

CNC

Diogo M. F. Mattos Brazil

Ahmed Alsayat Saudi Arabia

Karim Abouelmehdi Morocco

Neda Abdelhamid New Zealand

Praphula Kumar Jain India

Luigi Lo Iacono Germany

Mengmeng Yang China

Y. Ding China

Mahadevan Supramaniam Malaysia

Friedrich Steimann Germany

Diogo M. F. Mattos Brazil

Kim Wuyts

428 ×1.0

IS

121 ×0.4

SPS

384 ×1.3

AI

92 ×0.5

SP

623 ×4.5

CNC

Citations per year, relative to Kim Wuyts Kim Wuyts (= 1×) peers Diogo M. F. Mattos

Countries citing papers authored by Kim Wuyts

Since Specialization

Citations

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

Fields of papers citing papers by Kim Wuyts

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kim Wuyts

This figure shows the co-authorship network connecting the top 25 collaborators of Kim Wuyts. A scholar is included among the top collaborators of Kim Wuyts 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 Kim Wuyts. Kim Wuyts is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Sion, Laurens, Dimitri Van Landuyt, Kim Wuyts, & Wouter Joosen. (2025). Robust and reusable LINDDUN privacy threat knowledge. Computers & Security. 154. 104419–104419.

2.

Pallas, Frank, et al.. (2024). Privacy Engineering From Principles to Practice: A Roadmap. IEEE Security & Privacy. 22(2). 86–92. 3 indexed citations

3.

Wuyts, Kim, et al.. (2023). From insight to compliance: Appropriate technical and organisational security measures through the lens of cybersecurity maturity models. Computer law & security review. 52. 105914–105914. 8 indexed citations

4.

Al-Momani, Ala’a M., Christoph Bösch, Kim Wuyts, et al.. (2022). Mitigation lost in translation. Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing. 1236–1247. 1 indexed citations

5.

Al-Momani, Ala’a M., Kim Wuyts, Laurens Sion, et al.. (2021). Land of the lost: privacy patterns' forgotten properties. Lirias (KU Leuven). 1217–1225. 2 indexed citations

6.

Wuyts, Kim, Laurens Sion, & Wouter Joosen. (2020). LINDDUN GO: A Lightweight Approach to Privacy Threat Modeling. Lirias (KU Leuven). 302–309. 38 indexed citations

7.

Yskout, Koen, Thomas Heyman, Dimitri Van Landuyt, et al.. (2020). Threat modeling. Lirias (KU Leuven). 9–12. 6 indexed citations

8.

Sion, Laurens, et al.. (2019). DPMF: A Modeling Framework for Data Protection by Design. Lirias (KU Leuven). 4 indexed citations

9.

Wuyts, Kim, et al.. (2019). A comparison of system description models for data protection by design. Lirias (KU Leuven). 1512–1515. 8 indexed citations

10.

Sion, Laurens, Dimitri Van Landuyt, Kim Wuyts, & Wouter Joosen. (2019). Privacy Risk Assessment for Data Subject-Aware Threat Modeling. Lirias (KU Leuven). 64–71. 16 indexed citations

11.

Wuyts, Kim, Dimitri Van Landuyt, Aram Hovsepyan, & Wouter Joosen. (2018). Effective and efficient privacy threat modeling through domain refinements. Lirias (KU Leuven). 1175–1178. 24 indexed citations

12.

Wuyts, Kim. (2015). Privacy Threats in Software Architectures. 21 indexed citations

13.

Wuyts, Kim & Wouter Joosen. (2015). LINDDUN privacy threat modeling: a tutorial. Lirias (KU Leuven). 31 indexed citations

14.

Wuyts, Kim, Riccardo Scandariato, & Wouter Joosen. (2014). LIND(D)UN privacy threat tree catalog. Lirias (KU Leuven). 9 indexed citations

15.

Scandariato, Riccardo, Kim Wuyts, & Wouter Joosen. (2013). A descriptive study of Microsoft’s threat modeling technique. Requirements Engineering. 20(2). 163–180. 87 indexed citations

16.

Craenenbroeck, Emeline M. Van, Paul Beckers, Nadine Possemiers, et al.. (2010). Exercise acutely reverses dysfunction of circulating angiogenic cells in chronic heart failure. European Heart Journal. 31(15). 1924–1934. 63 indexed citations

17.

Wuyts, Kim, Thomas Heyman, Riccardo Scandariato, Christophe Huygens, & Wouter Joosen. (2010). Towards a reference framework for legal compliance: a detailed overview. Lirias (KU Leuven).

18.

Deng, Mina, Kim Wuyts, Riccardo Scandariato, Bart Preneel, & Wouter Joosen. (2010). A privacy threat analysis framework: supporting the elicitation and fulfillment of privacy requirements. Requirements Engineering. 16(1). 3–32. 308 indexed citations breakdown →

19.

Wuyts, Kim, Riccardo Scandariato, Bart De Decker, & Wouter Joosen. (2009). Linking Privacy Solutions to Developer Goals. Lirias (KU Leuven). 847–852. 9 indexed citations

20.

Wuyts, Kim, Riccardo Scandariato, Geert Claeys, & Wouter Joosen. (2008). Hardening XDS-Based Architectures. Lirias (KU Leuven). 18–25. 4 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.

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