TU Darmstadt / ULB / TUbiblio

Website operators are not the enemy either - Analyzing options for creating cookie consent notices without dark patterns

Stöver, Alina ; Gerber, Nina ; Cornel, Christin ; Henz, Mona ; Marky, Karola ; Zimmermann, Verena ; Vogt, Joachim (2022)
Website operators are not the enemy either - Analyzing options for creating cookie consent notices without dark patterns.
Mensch und Computer 2022. Darmstadt, Germany (04.-07.09.2022)
doi: 10.18420/muc2022-mci-ws01-458
Conference or Workshop Item, Bibliographie

Abstract

Users frequently receive cookie consent notices when they enter a website. They are supposed to enable an informed decision about data collection. Instead, they often contain deceptive designs - also known as dark patterns - that can nudge users to consent and thus compromise their privacy. In this paper, we explore the causes of the widespread use of dark patterns in cookie consents. To do so, we take the perspective of website operators, who are responsible for the use of cookie consent notices and are increasingly making use of Consent Management Platforms (CMPs) to manage end-user consent. CMPs usually contain certain design templates. To find out whether it is possible for website operators to generate notices without dark patterns using CMPs, we analyzed a selection of the templates offered by major CMPs. We show that 60% of the notices created with default settings contain at least one dark pattern. A notice that does not nudge toward a certain choice could only be generated with 62.5% of the CMPs. Our results imply that the responsibility for privacy-friendly notices lies more with the CMPs than with the website operators.

Item Type: Conference or Workshop Item
Erschienen: 2022
Creators: Stöver, Alina ; Gerber, Nina ; Cornel, Christin ; Henz, Mona ; Marky, Karola ; Zimmermann, Verena ; Vogt, Joachim
Type of entry: Bibliographie
Title: Website operators are not the enemy either - Analyzing options for creating cookie consent notices without dark patterns
Language: English
Date: 30 August 2022
Publisher: Gesellschaft für Informatik e.V.
Book Title: Mensch und Computer 2022 - Workshopband
Event Title: Mensch und Computer 2022
Event Location: Darmstadt, Germany
Event Dates: 04.-07.09.2022
DOI: 10.18420/muc2022-mci-ws01-458
Abstract:

Users frequently receive cookie consent notices when they enter a website. They are supposed to enable an informed decision about data collection. Instead, they often contain deceptive designs - also known as dark patterns - that can nudge users to consent and thus compromise their privacy. In this paper, we explore the causes of the widespread use of dark patterns in cookie consents. To do so, we take the perspective of website operators, who are responsible for the use of cookie consent notices and are increasingly making use of Consent Management Platforms (CMPs) to manage end-user consent. CMPs usually contain certain design templates. To find out whether it is possible for website operators to generate notices without dark patterns using CMPs, we analyzed a selection of the templates offered by major CMPs. We show that 60% of the notices created with default settings contain at least one dark pattern. A notice that does not nudge toward a certain choice could only be generated with 62.5% of the CMPs. Our results imply that the responsibility for privacy-friendly notices lies more with the CMPs than with the website operators.

Additional Information:

MCI-WS01: 8. Usable Security und Privacy Workshop

Divisions: DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 2050 Privacy and Trust for Mobile Users
Profile Areas
Profile Areas > Cybersecurity (CYSEC)
03 Department of Human Sciences
Forschungsfelder
Forschungsfelder > Information and Intelligence
Forschungsfelder > Information and Intelligence > Cybersecurity & Privacy
03 Department of Human Sciences > Institute for Psychology
03 Department of Human Sciences > Institute for Psychology > Engineering psychology research group!
Date Deposited: 19 Sep 2023 09:36
Last Modified: 26 Jan 2024 13:43
PPN: 509780679
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details