Multi-Range Supported Oblivious RAM for Efficient Block Data Retrieval
Yuezhi Che, Rujia Wang
Abstract
Data locality exists everywhere in the memory hierarchy. Most applications show temporal and spatial locality, and computer system and architecture designers utilize this property to improve the system performance with better data layout, prefetching, and scheduling. The locality property can be represented by memory access patterns, which records the time and frequency of accessed addresses. From the security perspective, if an attacker can trace the access pattern, sensitive information inside of the application could be observed and leaked. Oblivious RAM is one of the most effective solutions to mitigate the access pattern leakage on the system, which adds redundant data blocks in space and time. With ORAM protection, the intrinsic data locality is broken by the randomly stored data. Therefore, the application cannot gain any performance benefits from locality if the ORAM protocol is used. In this work, we would like to study the potential to support multi-range accesses with new storage and access efficient ORAM construction. Our proposed designs include two major schemes: Lite-rORAM, which minimize the storage overhead of existing rORAM; and Hybrid-rORAM, which support multiple ranges accesses with minimum storage overhead. We achieve the goal to preserve the locality for consecutive data blocks with different ranges in the application while obfuscates the access pattern as well. We tested our proposed schemes with different workloads on local and remote backends. The experimental results show that, in the best case, our proposed ORAM construction can reduce the data block retrieval time to 0.24x of the baseline Path ORAM, with 87.5% storage overhead reduction compared to rORAM.
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Install the CLIlune papers get 76b2df27-96ad-45fe-b8d3-7409733d0a3dCited by top-tier papers6
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- BOLT: Bandwidth-Optimized Lightning-Fast Oblivious Map powered by Secure HBM AcceleratorsYitong Guo, Hongbo Chen, Haobin Hiroki Chen, Yukui Luo et al.CCS 2025
- V-ORAM: A Versatile and Adaptive ORAM Framework with Service Transformation for Dynamic WorkloadsBo Zhang, Helei Cui, Xingliang Yuan, Zhiwen Yu et al.USENIX Security 2025
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