Kavli Affiliate: Hu Zhan
| First 5 Authors: Leqian Zheng, Lei Xu, Cong Wang, Sheng Wang, Yuke Hu
| Summary:
Numerous studies have underscored the significant privacy risks associated
with various leakage patterns in encrypted data stores. While many solutions
have been proposed to mitigate these leakages, they either (1) incur
substantial overheads, (2) focus on specific subsets of leakage patterns, or
(3) apply the same security notion across various workloads, thereby impeding
the attainment of fine-tuned privacy-efficiency trade-offs. In light of various
detrimental leakage patterns, this paper starts with an investigation into
which specific leakage patterns require our focus in the contexts of key-value,
range-query, and dynamic workloads, respectively. Subsequently, we introduce
new security notions tailored to the specific privacy requirements of these
workloads. Accordingly, we propose and instantiate SWAT, an efficient
construction that progressively enables these workloads, while provably
mitigating system-wide leakage via a suite of algorithms with tunable
privacy-efficiency trade-offs. We conducted extensive experiments and compiled
a detailed result analysis, showing the efficiency of our solution. SWATis
about an order of magnitude slower than an encryption-only data store that
reveals various leakage patterns and is two orders of magnitude faster than a
trivial zero-leakage solution. Meanwhile, the performance of SWATremains highly
competitive compared to other designs that mitigate specific types of leakage.
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