Journal
INFORMATION SCIENCES
Volume 479, Issue -, Pages 651-663Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2018.02.019
Keywords
Oblivious RAM; Partition ORAM; Private information retrieval
Categories
Funding
- National Natural Science Foundation of China [61472091, 61672300]
- National Natural Science Foundation of Tianjin [16JCYBJC15500]
- Natural Science Foundation of Guangdong Province for Distinguished Young Scholars [2014A030306020]
- Science and Technology Planning Project of Guangdong Province, China [2015B010129015]
- National Natural Science Foundation for Outstanding Youth Foundation [61722203]
- Ministry of Education and China Mobile Scientific Research Foundation [MCM20170403]
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Along with the popularity of outsourcing data to the cloud server, data privacy becomes a central consideration. Because encryption alone has been proved insecure for the leakages of access pattern, Oblivious RAM (ORAM) was proposed to protect where, when and how often the data block has been accessed. However, different types of ORAM implementations have different limitations in terms of significant bandwidth cost or massive storage space, making them impractical for some applications like Internet of Things (IoT). In this paper, we present a practical ORAM, called HybridORAM, with constant bandwidth, which can be applied in wide application scopes. HybridORAM explores a new ORAM design to combine the advantages of layer and tree ORAMs; more specifically, it combines the frequently-accessed small levels of the former to improve the response time, and the small shuffle of the latter to save the storage capacity. Compared to the typical schemes, HybridORAM has an efficient response time reduced by O(log k), low bandwidth cost optimized from O(IogN.B) to O(B) and small client storage, where k is level size factor, B is block size, N is the number of real blocks in ORAM. Experiments show that the response time of HybridORAM is 50.3% shorter than OnionORAM and 34.8% shorter than OS-PIR by practical parameters. (C) 2018 Elsevier Inc. All rights reserved.
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