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Detecting Bot Detection: Prevalence, Techniques, and Implications for Web Measurement Research

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arXiv:2606. 14525v1 Announce Type: new Abstract: Browser automation frameworks are essential tools for security and privacy research on the web, yet bot detection scripts increasingly probe their artifacts, threatening measurement validity as automated browsers may be blocked or served different content.

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Authors: Ralf Gundelach, Michael M\"uhlhauser, Dominik Herrmann
Released: 2026-06-15 (24d ago)
Topic: Related to current project
Relation to my work: Read next because Detecting Bot Detection: Prevalence, Techniques, and Implications for Web Measurement Research overlaps with clean result "Only continuous soft prefixes hit both EM axes at once on Qwen-2.5-7B-Instruct: discrete prompt searches split between the alignment objective and the distributional objective, and both discretizations of the soft prefix collapse (MODERATE confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe". Matching terms: soft, eval, rate, compare, alone. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2606.14525

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