Secure Boolean Spatial Keyword Query With Lightweight Access Control in Cloud Environments

Abstract

Spatial keyword query has attracted wide-spread academic and industrial concerns due to the popularity of location-based services and Internet of Things. To efficiently support the online query processing, the data owners need to outsource their data to cloud platforms. However, the outsourcing services may raise privacy leaking issues. Moreover, access control, another important security concern, is largely ignored. Therefore, we first propose and formalize the problem of secure boolean spatial keyword query under lightweight access control while guaranteeing the widely accepted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adaptive indistinguishability against chosen keyword attack</i> model. Then, we devise a novel hybrid Bloom filter encoding strategy, including a linear embedding and exponent-based transformation schemes and a secure index structure, called <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SAGTree</monospace> . They can maintain both geo-text and access policy information together in a secure way while answering the encrypted queries under access control without decryption. Finally, we present the in-depth security analysis and demonstrate the performance of our proposed algorithms.