Abstract
We propose a scheme for realizing privacy-preserving multidimensional range query on real-time data. This is motivated by the scenario where data owner (DO) stores its real-time data that are periodically submitted by its subordinate data collectors (DCs) on cloud service provider (CSP) in encrypted form and sometimes executes range query. The semi-trusted CSP is curious about the data and may return incomplete query results to DO. We divide time into \( N \) epochs and adopt key-insulated technology which supports periodical key update to bucketization method. Our scheme radically reduces the cost of DO and is more secure in the sense that keys for up to \( m < N \) epochs can be compromised without jeopardizing the security of whole system. Moreover, we realize the integrity verification of query results. Experiment results show that the cost of our scheme is acceptable, particularly for the scenario where each DC collects small amount of real-time data in each epoch.
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Acknowledgements
Our work is sponsored by the national natural science foundation of China (research on privacy protecting cipher text query algorithm in cloud storage, No. 61472064), the science and technology foundation of Sichuan province (research and application demonstration on trusted and safety-controllable privacy protecting service architecture for cloud data, 2015GZ0095) and the fundamental research funds for the central universities (research on some key technology in cloud storage security, YGX2013J072).
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Ting, Z., Xiao, H., Yunshuo, Y., Aixiang, Z. (2015). Privacy-Preserving Multidimensional Range Query on Real-Time Data. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_5
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