IACR News item: 22 September 2015
Hung Dang, Anh Dinh, Ee-Chien Chang, Beng Chin Ooi, Shruti Tople, Prateek Saxena
ePrint ReportThis paper proposes a practical system for privacy-preserving data management, called PRAMOD, in which data is stored in encrypted form and data-dependent computations are carried out inside a trusted environment. The system supports popular algorithms underlying many data management applications, including sort, compaction, join
and group aggregation. Data privacy is ensured even when data movement between different components (caused by limited private memory) is observed by the adversary. For many algorithms, this is achieved by appending a component called scrambler which breaks the linkage between the input and output. Our experimental study indicates reasonable overheads over a baseline system with a weaker level of security. In addition, PRAMOD shows better performance
than state-of-the-art solutions with similar levels of security. For example, PRAMOD achieves 4.4× speedup over the alternative data-oblivious sorting algorithm.
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