Collaborative Privacy for Web Applications
Yihao Hu, Ari Trachtenberg, Prakash Ishwar

TL;DR
This paper introduces a privacy-preserving system for collaborative web applications, enabling users to encrypt data locally and collaboratively edit documents without revealing plaintext to service providers.
Contribution
It presents a novel character-level encryption scheme and a browser extension that allows encrypted collaboration on Google Docs without server-side access to plaintext.
Findings
Successfully implemented a Chrome extension for encrypted Google Docs editing.
Demonstrated resilience of the encryption scheme against common attacks.
Showed practical feasibility of privacy-preserving collaboration in real-world web apps.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInternet Traffic Analysis and Secure E-voting · Privacy, Security, and Data Protection · Advanced Malware Detection Techniques
