Privacy-Preserving Ranked Search on Public-Key Encrypted Data

The massive production of digital data and the complexity of the underlying data management, motivate individuals and enterprises to outsource their computational needs to the cloud. While popular cloud computing platforms provide flexible and inexpensive solutions, they do so with minimal support for data security and privacy. As a result, owners of sensitive information may be skeptical in purchasing such services, given the risks associated with the unauthorized access to their data. To this end, searchable encryption is a family of cryptographic protocols that facilitate private keyword searches directly on encrypted data. These protocols allow users to upload encrypted versions of their documents to the cloud, while retaining the ability to query the database with traditional plaintext keyword queries. In this paper, we focus on public-key encrypted data and introduce the first method that supports ranked results from multi-keyword searches. Our solution employs a simple indexing structure, and leverages homomorphic encryption and private information retrieval (PIR) protocols to process queries in a privacy-preserving manner. Using measurements from Amazon's Elastic Compute Cloud, we show that our method provides reasonable response times with low communication cost.