Cuckoo-Filter Based Privacy-Aware Search over Encrypted Cloud Data

Abstract

Many organizations and individual users are out-sourcing their information which includes sensitive data into the cloud. To deal with the potential risks of privacy exposure, such data is typically encrypted before being outsourced but users would like to conduct keyword-based searches. Traditional searchable encryption techniques are overly restrictive for they only allow exact keyword search. Thus, fuzzy keyword search is needed to deal with typos in users' search strings. In this paper, we present a Cuckoo Filter Based Private Keyword Search Scheme (CFPKS) to provide privacy-aware keyword search over encrypted data. This CFPKS scheme uses a bed-tree structure-based index to boost search efficiency, a wildcard approach to support fuzzy keyword search, and a Cuckoo-filter to improve search accuracy and storage efficiency. Our scheme handles both typos and query unlinkability. Using a large ACM publication dataset, the evaluation results comparing the search efficiency and accuracy of our proposed CFPKS scheme with three existing schemes show that our scheme achieves higher search accuracy with lower search cost.