Dual Protection Ring: User Profiling Via Differential Privacy and Service Dissemination Through Private Information Retrieval

TL;DR

This paper introduces a dual protection mechanism combining differential privacy and private information retrieval to safeguard user profiling data while enabling personalized services, demonstrated through a mobile app case study.

Contribution

It presents a novel dual-ring privacy protection framework integrating differential privacy and PIR, addressing multiple privacy threats in user profiling systems.

Findings

Profiles with differential privacy effectively protect sensitive attributes.

PIR schemes enable personalized service retrieval with minimal delay.

The approach is practical and scalable for real-world applications.

Abstract

User profiling is crucial in providing personalised services, as it relies on analysing user behaviour and preferences to deliver targeted services. This approach enhances user experience and promotes heightened engagement. Nevertheless, user profiling also gives rise to noteworthy privacy considerations due to the extensive tracking and monitoring of personal data, potentially leading to surveillance or identity theft. We propose a dual-ring protection mechanism to protect user privacy by examining various threats to user privacy, such as behavioural attacks, profiling fingerprinting and monitoring, profile perturbation, etc., both on the user and service provider sides. We develop user profiles that contain sensitive private attributes and an equivalent profile based on differential privacy for evaluating personalised services. We determine the entropy of the resultant profiles during each update to protect profiling attributes and invoke various processes, such as data evaporation, to artificially increase entropy or destroy private profiling attributes. Furthermore, we use different variants of private information retrieval (PIR) to retrieve personalised services against differentially private profiles. We implement critical components of the proposed model via a proof-of-concept mobile app to demonstrate its applicability over a specific case study of advertising services, which can be generalised to other services. Our experimental results show that the observed processing delays with different PIR schemes are similar to the current advertising systems.