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Audio CAPTCHAs are supposed to provide a strong defense for online resources;however, advances in speech-to-text mechanisms have rendered these defensesineffective. Audio CAPTCHAs cannot simply be abandoned, as they arespecifically named by the W3C as important enablers of accessibility.Accordingly, demonstrably more robust audio CAPTCHAs are important to thefuture of a secure and accessible Web. We look to recent literature on attackson speech-to-text systems for inspiration for the construction of robust,principle-driven audio defenses. We begin by comparing 20 recent attack papers,classifying and measuring their suitability to serve as the basis of new"robust to transcription" but "easy for humans to understand" CAPTCHAs. Aftershowing that none of these attacks alone are sufficient, we propose a newmechanism that is both comparatively intelligible (evaluated through a userstudy) and hard to automatically transcribe (i.e., $P({\rm transcription}) = 4\times 10^{-5}$). Finally, we demonstrate that our audio samples have a highprobability of being detected as CAPTCHAs when given to speech-to-text systems($P({\rm evasion}) = 1.77 \times 10^{-4}$). In so doing, we not onlydemonstrate a CAPTCHA that is approximately four orders of magnitude moredifficult to crack, but that such systems can be designed based on the insightsgained from attack papers using the differences between the ways that humansand computers process audio.

Attacks as Defenses: Designing Robust Audio CAPTCHAs Using Attacks on Automatic Speech Recognition Systems