Work

PProx

Year: 2021

Type: conference-paper

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 Harness's Universal Recommender 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.

Source: International Middleware Conference

DOI: 10.1145/3464298.3476130

Authors: Guillaume Rosinosky, Simon Da Silva, Sonia Ben Mokhtar, Daniel Négru, Laurent Réveillère, Etienne Rivière