Abstract
Software systems have become an integral part of our daily lives. However, users tend to forget that they are not only consuming information, but also delivering personal information to service providers. This data collection means that users' privacy sphere is increasingly at stake. Informing users about what and how data is collected is pivotal for reaching transparency, trustworthiness, and ethics in modern systems. The main purpose of privacy policies is to inform users about what happens to their personal data. But instead they are extensive and purposefully obfuscating. Information about data practices are hidden in long and ambiguous text passages. To mitigate this, in this paper, we present a concept implemented as a web extension to support the end-user in dealing with privacy policies by providing easier access and visual explanations to privacy-related information. We evaluated the usefulness of our tool in a user study with 65 participants. The results show that our approach helps users to find a privacy policy faster and also supports users to better comprehend the relevant information. Our tool is a first step towards facilitating to deal with privacy policies from the end-user perspective. The results of the study and the positive feedback from the participants show a high degree of acceptance and potential for the tool to increase users' privacy awareness.
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings - 2022 IEEE/ACM Joint 16th International Conferenceon Software and System Processes and 17th ACM/IEEE International Conference on Global Software Engineering, ICSSP/ICGSE 2022 |
| Untertitel | ICSSP'22 |
| Erscheinungsort | Pittsburgh, PA, USA |
| Herausgeber (Verlag) | ACM DL |
| Seiten | 56–65 |
| Seitenumfang | 10 |
| ISBN (elektronisch) | 9781450396745 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 19 Mai 2022 |
Publikationsreihe
| Name | ACM International Conference Proceeding Series |
|---|
ASJC Scopus Sachgebiete
- Software
- Mensch-Maschine-Interaktion
- Maschinelles Sehen und Mustererkennung
- Computernetzwerke und -kommunikation
Projekte
- 1 Abgeschlossen
-
PhoenixD: Exzellenzcluster 2122/1: Photonics, Optics, and Engineering – Innovation Across Disciplines
Morgner, U. (Projektleiter*in (Principal Investigator)) & Overmeyer, L. (Leitende*r Forscher*in (Co-Principal Investigator))
1 Jan. 2019 → 31 Dez. 2025
Projekt: Forschung
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