Linddun
LINDDUN is a privacy-focused threat modeling framework that systematically identifies and analyzes privacy threats in software systems by applying seven distinct categories of threats—Linkability, Identifiability, Non-repudiation, Detectability, Disclosure of information, Unawareness, and Non-compliance.
14
Publications
505
Citations
23
Authors
12
Institutions
Publications per year
2017–2026
11
Parents
14
On the privacy of mental health apps
Leonardo Horn Iwaya, Muhammad Ali Babar, Awais Rashid et al. · Empirical Software Engineering · 2022 · 88 citations · Full text
LINDDUN GO: A Lightweight Approach to Privacy Threat Modeling
Kim Wuyts, Laurens Sion, Wouter Joosen · 2020 · 71 citations · Full text
Solution-aware data flow diagrams for security threat modeling
Laurens Sion, Koen Yskout, Dimitri Van Landuyt et al. · 2018 · 55 citations · Full text
LINDDUN privacy threat modeling: a tutorial
Kim Wuyts, Wouter Joosen · Lirias (KU Leuven) · 2015 · 43 citations · Full text
Privacy Threats in Software Architectures
Kim Wuyts · 2015 · 41 citations
Computing, Computer Science, Design +13
1–5 of 14
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12
KU Leuven
Leuven, Belgium
8 h-index
20 publications
866 citations
IMEC
Leuven, Belgium
4 h-index
16 publications
722 citations
Institut de Recherche Technologique SystemX
Palaiseau, France
1 h-index
2 publications
40 citations
Harm Reduction Services
Sacramento, United States
1 h-index
1 publications
88 citations

Universitat Rovira i Virgili
Tarragona, Spain
1 h-index
1 publications
22 citations
Fraunhofer Institute for Applied and Integrated Security
Garching, Germany
1 h-index
4 publications
60 citations
Karlstad University
Karlstad, Sweden
1 h-index
1 publications
88 citations

University of Duisburg-Essen
Essen, Germany
1 h-index
1 publications
36 citations
1–8 of 12
1 publications · 22 citations
2
h-index
Repository · 1 publications · 43 citations
1
h-index
PoPETs · 1 publications · 15 citations
1
h-index
1 publications · 88 citations
1
h-index
1 publications · 20 citations
1
h-index
1–5