CRJan 10, 2019

Collaborative Privacy for Web Applications

arXiv:1901.03383v21 citations
AI Analysis

This addresses privacy concerns for users of collaborative web apps like Google Docs, though it is an incremental improvement focused on a specific domain.

The paper tackles the privacy risks in real-time collaborative web applications by proposing a character-level encryption scheme and a browser extension, demonstrating that users can collaboratively edit Google Docs without revealing plaintext to the service provider.

Real-time, online-editing web apps provide free and convenient services for collaboratively editing, sharing and storing files. The benefits of these web applications do not come for free: not only do service providers have full access to the users' files, but they also control access, transmission, and storage mechanisms for them. As a result, user data may be at risk of data mining, third-party interception, or even manipulation. To combat this, we propose a new system for helping to preserve the privacy of user data within collaborative environments. There are several distinct challenges in producing such a system, including developing an encryption mechanism that does not interfere with the back-end (and often proprietary) control mechanisms utilized by the service, and identifying transparent code hooks through which to obfuscate user data. Toward the first challenge, we develop a character-level encryption scheme that is more resilient to the types of attacks that plague classical substitution ciphers. For the second challenge, we design a browser extension that robustly demonstrates the feasibility of our approach, and show a concrete implementation for Google Chrome and the widely-used Google Docs platform. Our example tangibly demonstrates how several users with a shared key can collaboratively and transparently edit a Google Docs document without revealing the plaintext directly to Google.

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