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Dark Patterns in the Wild: Review of Cookie Disclaimer Designs on Top 500 German Websites

Krisam, Chiara ORCID iD icon; Dietmann, Heike; Volkamer Melanie; Kulyk, Oksana

Abstract:

Cookie disclaimers are these days an indispensable part of surfing and working on the Internet. In this work, we report on examining and classifying the cookie disclaimers on the 500 most popular websites in Germany, based on the presented information about data collection via cookies and the provided choices at the cookie disclaimer. Our analysis results in 13 categories of cookie disclaimers, consisting of six main categories and additional subcategories. Our findings include that dark pattern based categories were prevalent among the cookie disclaimers: e.g. (1) more than 85\% of the investigated websites providing a cookie disclaimer and giving the option to reject cookies are visually nudging users towards accepting all cookies; (2) Only 21.5\% of those providing a cookie disclaimer offer a reject-all option with a single click.
We discuss our results and conclude that both raising user awareness as well as addressing dark patterns from a legal point of view is needed.


Postprint §
DOI: 10.5445/IR/1000136334
Veröffentlicht am 12.10.2022
Originalveröffentlichung
DOI: 10.1145/3481357.3481516
Scopus
Zitationen: 25
Dimensions
Zitationen: 29
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Institut für Wirtschaftsinformatik und Marketing (IISM)
Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 11.12.2021
Sprache Englisch
Identifikator ISBN: 978-1-4503-8423-0
KITopen-ID: 1000136334
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Erschienen in EuroUSEC '21: European Symposium on Usable Security 2021, Karlsruhe Germany, October 11 - 12, 2021
Veranstaltung European Symposium on Usable Security (EuroUSEC 2021), Online, 11.10.2021 – 12.10.2021
Verlag Association for Computing Machinery (ACM)
Seiten 8 S.
Vorab online veröffentlicht am 11.10.2021
Nachgewiesen in Dimensions
Scopus
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