  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.
