Privacy-aware Document Search on the Cloud
As sensitive information is increasingly stored on the cloud, privacy protection is a critical factor for users to adopt cloud-based information services such as document search. A cloud server can observe the client-initiated query processing flow, extract statistical patterns, and reason about client's data. As a result, the risk of leakage-abuse attacks exists when searching on the cloud. The main challenge to perform privacy-preserving search is that index visitation can reveal sensitive data patterns, and computation involved in advanced ranking can further expose private feature information. On the other hand, hiding index and feature information through full encryption prevents the server from performing effective scoring and result comparison.
This project studies algorithmic indexing and ranking solutions for privacy-aware cloud document search.
Publication and other project materials
Acknowledgment: This material is based upon work supported by the National Science Foundation 2040146 (2020-2022). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Last update: July 28, 2020