Evaluating the Efficacy of LINDDUN GO for Privacy Threat Modeling for Local Renewable Energy Communities

Oliver Langthaler, Günther Eibl, Lars-Kevin Klüver, Andreas Unterweger

2025

Abstract

While security is considered an essential aspect of the design and implementation of many systems, privacy is often overlooked, especially in early planning phases. Although methodologies for the identification of privacy threats have been proposed, the number of studies outlining their practical application is limited. As a consequence, practical experience with these methods is sparse. This raises questions about their practicality and applicability for the energy domain. As a first step towards the assessment of the practical properties, we apply a lightweight version of the most prominent methodology, LINDDUN GO, to an intelligent charging use case for local renewable energy communities that is based on load forecasting. We find that one of the main advantages of LINDDUN GO is the completeness of the analysis, which was able to identify not only a built-in privacy deficiency but also unforeseen privacy threats for the considered use case. However, we also found that LINDDUN GO is not applicable for all privacy categories: Detectability was not assessable since it required detailed information that was not contained in our data flow graph in the design phase. In contrast, non-compliance was treated too generically, its intention is more to complete the list of important topics.

Paper Citation

in Harvard Style

Langthaler O., Eibl G., Klüver L. and Unterweger A. (2025). Evaluating the Efficacy of LINDDUN GO for Privacy Threat Modeling for Local Renewable Energy Communities. In Proceedings of the 11th International Conference on Information Systems Security and Privacy - Volume 2: ICISSP; ISBN 978-989-758-735-1, SciTePress, pages 518-525. DOI: 10.5220/0013163000003899

in Bibtex Style

@conference{icissp25,
author={Oliver Langthaler and Günther Eibl and Lars-Kevin Klüver and Andreas Unterweger},
title={Evaluating the Efficacy of LINDDUN GO for Privacy Threat Modeling for Local Renewable Energy Communities},
booktitle={Proceedings of the 11th International Conference on Information Systems Security and Privacy - Volume 2: ICISSP},
year={2025},
pages={518-525},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013163000003899},
isbn={978-989-758-735-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Information Systems Security and Privacy - Volume 2: ICISSP
TI - Evaluating the Efficacy of LINDDUN GO for Privacy Threat Modeling for Local Renewable Energy Communities
SN - 978-989-758-735-1
AU - Langthaler O.
AU - Eibl G.
AU - Klüver L.
AU - Unterweger A.
PY - 2025
SP - 518
EP - 525
DO - 10.5220/0013163000003899
PB - SciTePress