PProx

Abstract

We present PProx, a system preventing recommendation-as-a-service (RaaS) providers from accessing sensitive data about the users of applications leveraging their services. PProx does not impact recommendations accuracy, is compatible with arbitrary recommendation algorithms, and has minimal deployment requirements. Its design combines two proxying layers directly running inside SGX enclaves at the RaaS provider side. These layers transparently pseudonymize users and items and hide links between the two, and PProx privacy guarantees are robust even to the corruption of one of these enclaves. We integrated PProx with the Harness recommendation engine and evaluated it on a 27-node cluster. Our results indicate its ability to withstand a high number of requests with low end-to-end latency, horizontally scaling up to match increasing workloads of recommendations.CCS Concepts • Security and privacy;

Privacy-preserving techniques in recommender systems: state-of-the-art review and future research agenda

“…PProx (privacy-preserving proxy) system uses two proxying layers at the server-side, which pseudonymizes users and items transparently and hides the links between them. This prevents sensitive data access, and the service is robust even if one of the enclaves is corrupted (Rosinosky et al , 2021). There is a possibility that the system's accuracy gets affected while preserving privacy.…”