Scalable Private Search with Wally

This paper presents Wally, a private search system that supports efficient semantic and keyword search queries against large databases. When sufficiently many clients are making queries, Wally's performance is significantly better than previous systems. In previous private search systems, for each client query, the server must perform at least one expensive cryptographic operation per database entry. As a result, performance degraded proportionally with the number of entries in the database. In Wally, we get rid of this limitation. Specifically, for each query the server performs cryptographic operations only against a few database entries. We achieve these results by requiring each client to add a few fake queries and send each query via an anonymous network to the server at independently chosen random instants. Additionally, each client also uses somewhat homomorphic encryption (SHE) to hide whether a query is real or fake. Wally provides $(\epsilon, \delta)$-differential privacy guarantee, which is an accepted standard for strong privacy. The number of fake queries each client makes depends inversely on the number of clients making queries. Therefore, the fake queries' overhead vanishes as the number of clients increases, enabling scalability to millions of queries and large databases. Concretely, Wally can process eight million queries in just 117 mins. That is around four orders of magnitude less than the state of the art.