Title
PProx: efficient privacy for recommendation-as-a-service
Abstract
ABSTRACTWe 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.
Year
DOI
Venue
2021
10.1145/3464298.3476130
MIDDLEWARE
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Guillaume Rosinosky100.34
Simon Da Silva201.69
Sonia Ben Mokhtar359644.86
Daniel Negru48619.91
Laurent Réveillère525126.35
Etienne Rivière600.34