Abstract
We propose a secure yet efficient data query system for cloud-based key-value store. Our system supports encryption and compression to ensure confidentiality and query efficiency simultaneously. To reconcile encryption and compression without compromising performance, we propose a new encrypted key-value storage structure based on the concept of horizontal-vertical division. Our storage structure enables fine-grained access to compressed yet encrypted key-value data. We further combine several cryptographic primitives to build secure search indexes on the storage structure. As a result, our system supports rich types of queries including key-value query and range query. We implement a prototype of our system on top of Cassandra. Our evaluation shows that our system increases the throughput by up to 7 times and compression ratio by up to 1.3 times with respect to previous works.
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Acknowledgement
We acknowledge the support from National Natural Science Foundation of China (Nos. 61602363 and 61572382), China 111 Project (No. B16037) and China Postdoctoral Science Foundation (No. 2016M590927).
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Zhang, M., Qi, S., Miao, M., Zhang, F. (2019). Enabling Compressed Encryption for Cloud Based Big Data Stores. In: Mu, Y., Deng, R., Huang, X. (eds) Cryptology and Network Security. CANS 2019. Lecture Notes in Computer Science(), vol 11829. Springer, Cham. https://doi.org/10.1007/978-3-030-31578-8_15
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