3PS - Online Privacy through Group Identities

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 time in our tests, while protecting plausible deniability effectively in the face of worst-case threats from a variety of attack types.