Using Salient Object Detection to Identify Manipulative Cookie Banners that Circumvent GDPR
Riley Grossman, Michael Smith, Cristian Borcea, Yi Chen

TL;DR
This study investigates how often cookie banners use aesthetic manipulation to influence user behavior, revealing that such tactics are more common than previously thought, especially in EU websites where regulations are stricter.
Contribution
The paper introduces a computer vision model to quantify banner salience, uncovering new manipulation techniques and providing a comparative analysis of EU and non-EU website practices.
Findings
38% of compliant banners use aesthetic manipulation
EU websites are 48.3% more likely to employ manipulation
13.9% of EU websites change design based on user location
Abstract
The main goal of this paper is to study how often cookie banners that comply with the General Data Protection Regulation (GDPR) contain aesthetic manipulation, a design tactic to draw users' attention to the button that permits personal data sharing. As a byproduct of this goal, we also evaluate how frequently the banners comply with GDPR and the recommendations of national data protection authorities regarding banner designs. We visited 2,579 websites and identified the type of cookie banner implemented. Although 45% of the relevant websites have fully compliant banners, we found aesthetic manipulation on 38% of the compliant banners. Unlike prior studies of aesthetic manipulation, we use a computer vision model for salient object detection to measure how salient (i.e., attention-drawing) each banner element is. This enables the discovery of new types of aesthetic manipulation (e.g.,…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Innovative Human-Technology Interaction · Ethics and Social Impacts of AI
