Abstract
To fully benefit from a cloud storage approach, privacy in outsourced databases needs to be preserved in order to protect information about individuals and organisations from malicious cloud providers. As shown in recent studies [1, 2], encryption alone is insufficient to prevent a malicious cloud provider from analysing data access patterns and mounting statistical inference attacks on encrypted databases. In order to thwart such attacks, actions performed on outsourced databases need to be oblivious to cloud service providers. Approaches, such as Fully Homomorphic Encryption (FHE), Oblivious RAM (ORAM), or Secure Multi-Party Computation (SMC) have been proposed but they are still not practical. This paper investigates and proposes a practical privacy-preserving scheme, named Long White Cloud (LWC), for outsourced databases with a focus on providing security against statistical inferences. Performance is a key issue in the search and retrieval of encrypted databases. LWC supports logarithmic-time insert, search and delete queries executed by outsourced databases with minimised information leakage to curious cloud service providers. As a proof-of-concept, we have implemented LWC and compared it with a plaintext MySQL database: even with a database size of 10M records, our approach shows only a 10-time slowdown factor.
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Cui, S., Zhang, M., Asghar, M.R., Russello, G. (2018). Long White Cloud (LWC): A Practical and Privacy-Preserving Outsourced Database. In: Hancke, G., Damiani, E. (eds) Information Security Theory and Practice. WISTP 2017. Lecture Notes in Computer Science(), vol 10741. Springer, Cham. https://doi.org/10.1007/978-3-319-93524-9_3
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DOI: https://doi.org/10.1007/978-3-319-93524-9_3
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