Abstract
In the past decades, with the development of cloud computing, ranked keyword search, which devotes to find the most relevant results, has been extensively studied in outsourcing domain. However, due to a mass of sensitive information containing in the outsourced data, the issue of privacy has become the main brunt. Existing works primarily resort to searchable encryption to protect the privacy but do not consider the access pattern and search pattern, which can be used to infer the privacy information. Moreover, since the cloud server may be malicious, result integrity also needs to be considered. Therefore, in this paper, we study the problem of secure and authenticated ranked keyword search, called SARKS. Specifically, we first propose a framework that integrates d-differential privacy, erasure coding, and oblivious traverse to achieve access pattern and search pattern protection and meanwhile propose a scheme based on merkle hash tree to realize the correctness and completeness of the query results. To accelerate the performance, we further propose an improved scheme by adopting clustering method. Finally, the formal security analysis is conducted and the empirical evaluation over the real-world dataset has demonstrated the feasibility and practicability of our proposed schemes.
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Acknowledgement
This work was supported by National Natural Science Foundation of China (62011530-046, U1936220, 62002054), Industry-university-research Innovation Fund for Chinese Universities (2020ITA03009), Ten Thousand Talent Program (ZX20200035), and Excellent Youth Foundation of Anhui Scientific Committee (2108085J31).
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Cui, N., Deng, Z., Li, M., Ma, Y., Cui, J., Zhong, H. (2023). Authenticated Ranked Keyword Search over Encrypted Data with Strong Privacy Guarantee. In: Wang, X., et al. Database Systems for Advanced Applications. DASFAA 2023. Lecture Notes in Computer Science, vol 13943. Springer, Cham. https://doi.org/10.1007/978-3-031-30637-2_43
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