Fingerprint surface-based detection of web bot detectorsThis website provides additional materials to our research published at ESORICS 2019. A preprint version is available here. This project aims to explore web bot detection based on technical properties by fingerprinting bots.
We base our research on a reverse analysis of a commercial bot detector. This showed that unique properties web clients exist which that sufficient to identify a web bot. We developed a more general approach to find system properties of web bots that allow us to distinguish these from human-controlled web clients. Our developed methodology comprises browser fingerprinting and comparisons of resulting fingerprints of a regular browser and web bot frameworks that belong to the same browser family. The derived fingerprint surfaces of web bots were used to conduct the first measurement of the prevalence of web bot detection in the Web. Responsible for this project are: Responsible for this project are:
Hugo Jonker and