3PS - Online Privacy through Group Identities
Pol Mac Aonghusa, Douglas Leith

TL;DR
This paper introduces 3PS, a system of group identities that enables personalized online content while preserving user privacy and plausible deniability, challenging the necessity of broad data collection.
Contribution
The paper develops formal models of privacy and utility, and presents a prototype demonstrating effective personalization and privacy protection using group identities.
Findings
Provides personalized content over 98% of the time in tests
Effectively protects plausible deniability against various attacks
Demonstrates that broad data collection is not necessary for personalization
Abstract
Limiting online data collection to the minimum required for specific purposes is mandated by modern privacy legislation such as the General Data Protection Regulation (GDPR) and the California Consumer Protection Act. This is particularly true in online services where broad collection of personal information represents an obvious concern for privacy. We challenge the view that broad personal data collection is required to provide personalised services. By first developing formal models of privacy and utility, we show how users can obtain personalised content, while retaining an ability to plausibly deny their interests in topics they regard as sensitive using a system of proxy, group identities we call 3PS. Through extensive experiment on a prototype implementation, using openly accessible data sources, we show that 3PS provides personalised content to individual users over 98% of the…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data · Privacy, Security, and Data Protection · Internet Traffic Analysis and Secure E-voting
