Dark Patterns in the Interaction with Cookie Banners
This work addresses the issue of user manipulation online, but it appears incremental as it builds on existing research in dark pattern detection.
The paper tackles the problem of automatically detecting dark patterns in cookie banners to protect web users from malicious interface designs, presenting ongoing work and an example detection approach.
Dark patterns are interface designs that nudge users towards behavior that is against their best interests. Since humans are often not even aware that they are influenced by these malicious patterns, research has to identify ways to protect web users against them. One approach to this is the automatic detection of dark patterns which enables the development of tools that are able to protect users by proactively warning them in cases where they face a dark pattern. In this paper, we present ongoing work in the direction of automatic detection of dark patterns, and outline an example to detect malicious patterns within the domain of cookie banners.