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Title: Only Pay for What You Leak: Leveraging Sandboxes for a Minimally Invasive Browser Fingerprinting Defense
Authors: Torok, Ryan Daniel
Advisors: Levy, Amit A
Department: Computer Science
Class Year: 2023
Publisher: Princeton, NJ : Princeton University
Abstract: We present Sandcastle, an entropy-based browser fingerprinting defense that aims to minimize its interference with legitimate web applications. Sandcastle allows developers to partition code that operates on identifiable information into sandboxes to prove to the browser the information cannot be sent in any network request. Meanwhile, sandboxes may make full use of identifiable information on the client side, including writing to dedicated regions of the Document Object Model. For applications where this policy is too strict, Sandcastle provides an expressive cashier that allows precise control over the granularity of data that is leaked to the network. These features allow Sandcastle to eliminate most or all of the noise added to the outputs of identifiable APIs by Chrome’s Privacy Budget framework, the current state of the art in entropy-based fingerprinting defenses. Enabling unlimited client-side use of identifiable information allows for a much more comprehensive set of web applications to run under a fingerprinting defense, such as 3D games and video streaming, and provides a mechanism to expand the space of APIs that can be introduced to the web ecosystem without sacrificing privacy.
Language: en
Appears in Collections:Computer Science, 2023

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