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. Most existing systems
that conceal leakage 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 respectively in the contexts of key-value,
range-query, and dynamic workloads. Subsequently, we introduce new security
notions tailored to the specific privacy requirements of these workloads.
Accordingly, we present, 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. SWAT is about $10.6times$ slower than an
encryption-only data store that reveals various leakage patterns and is
$31.6times$ faster than a trivially zero-leakage solution. Meanwhile, the
performance of SWAT remains highly competitive compared to other designs that
mitigate specific types of leakage.
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