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Recent studies show that 20.4% of the internet traffic originates fromautomated agents. To identify and block such ill-intentioned traffic,mechanisms that verify the humanness of the user are widely deployed, withCAPTCHAs being the most popular. Traditional CAPTCHAs require extra user effort(e.g., solving mathematical puzzles), which can severely downgrade theend-user's experience, especially on mobile, and provide sporadic humannessverification of questionable accuracy. More recent solutions like Google'sreCAPTCHA v3, leverage user data, thus raising significant privacy concerns. Toaddress these issues, we present zkSENSE: the first zero-knowledge proof-basedhumanness attestation system for mobile devices. zkSENSE moves the humanattestation to the edge: onto the user's very own device, where humanness ofthe user is assessed in a privacy-preserving and seamless manner. zkSENSEachieves this by classifying motion sensor outputs of the mobile device, basedon a model trained by using both publicly available sensor data and datacollected from a small group of volunteers. To ensure the integrity of theprocess, the classification result is enclosed in a zero-knowledge proof ofhumanness that can be safely shared with a remote server. We implement zkSENSEas an Android service to demonstrate its effectiveness and practicality. In ourevaluation, we show that zkSENSE successfully verifies the humanness of a useracross a variety of attacking scenarios and demonstrates 92% accuracy. On a twoyears old Samsung S9, zkSENSE's attestation takes around 3 seconds (when visualCAPTCHAs need 9.8 seconds) and consumes a negligible amount of battery.

ZKSENSE: A Friction-less Privacy-Preserving Human Attestation Mechanism for Mobile Devices