Welcome to the resource topic for 2025/1938
Title:
zk-Cookies: Continuous Anonymous Authentication for the Web
Authors: Alexander Frolov, Hal Triedman, Ian Miers
Abstract:We are now entering an era where the large-scale deployment of anonymous credentials seems inevitable, driven both by legislation requiring age verification and the desire to distinguish humans from bots in the face of the proliferation of AI-generated content. However, the widespread deployment of anonymous credentials faces the same security and fraud concerns as existing credentials, but without the established techniques for securing them. For non-anonymous credentials on the web today, authentication is a continuous process in which servers collect large volumes of behavioral data to protect account holders (e.g., by detecting account compromise) or to combat fraudulent behavior.
In this paper, we propose Continuous Anonymous Authentication (CAA) schemes and give a concrete construction and applications for preventing credential sharing and theft. CAA schemes allow us to move the server-side collection, storage, and processing of these behavioral signals to the client while maintaining privacy and integrity. CAA schemes support, on the client side, a number of common behavioral analysis tests and analytics both for determining fraudulent behavior and updating security policies. We implement a prototype, zk-Cookies, which runs in the browser, and supports common behavioral signals such as IP address and geolocation history, browser fingerprinting, and page view history. Using this, we build a prototype application for age verification based on legacy credentials (like passports). We implement these checks efficiently in zk-SNARKs, and also show how to securely implement differentially private behavioral analytics in a zk-SNARK. The simplest version of our construction can perform the computation for an update in under 200 ms.
ePrint: https://eprint.iacr.org/2025/1938
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