Streamline Ring ORAM Accesses through Spatial and Temporal Optimization
Dingyuan Cao, Mingzhe Zhang, Hang Lu, Xiaochun Ye, Dongrui Fan, Yuezhi Che, Rujia Wang
摘要
Memory access patterns could leak temporal and spatial information in a sensitive program; therefore, obfuscated memory access patterns are desired from the security perspective. Oblivious RAM (ORAM) has been the favored candidate to eliminate the access pattern leakage through randomly remapping data blocks around the physical memory space. Meanwhile, accessing memory with ORAM protocols results in significant memory bandwidth overhead. For each memory request, after going through the ORAM obfuscation, the main memory needs to service tens of actual memory accesses, and only one real access out of them is useful for the program execution. Besides, to ensure the memory bus access patterns are indistinguishable, extra dummy blocks need to be stored and transmitted, which cause memory space waste and poor performance.
In this work, we introduce a new framework, String ORAM, that accelerates the Ring ORAM accesses with Spatial and Temporal optimization schemes. First, we identify that dummy blocks could significantly waste memory space and propose a compact ORAM organization that leverages the real blocks in memory to obfuscate the memory access pattern. Then, we identify the inefficiency of current transaction-based Ring ORAM scheduling on DRAM devices and propose an effective scheduling technique that can overlap the time spent on row buffer misses while ensuring correctness and security. With a minimal modification on the hardware and software, and negligible impact on security, the framework reduces 30.05% execution time and up to 40% memory space overhead compared to the state-of-the-art bandwidth-efficient Ring ORAM.
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引用它的顶会 Paper7
- GPU-based Private Information Retrieval for On-Device Machine Learning InferenceMaximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng 等ASPLOS 2024 · 被引用 11 次
- AB-ORAM: Constructing Adjustable Buckets for Space Reduction in Ring ORAMMehrnoosh Raoufi, Jun Yang, Xulong Tang, Youtao ZhangHPCA 2023 · 被引用 7 次
- LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding TablesRachit Rajat, Yongqin Wang, Murali AnnavaramISCA 2023 · 被引用 6 次
- Practical Federated Recommendation Model Learning Using ORAM with Controlled PrivacyJinyu Liu, Wenjie Xiong, G. Edward Suh, Kiwan MaengASPLOS 2025 · 被引用 2 次
- EP-ORAM: Efficient NVM-Friendly Path Eviction for Ring ORAM in Hybrid MemoryMehrnoosh Raoufi, Jun Yang, Xulong Tang, Youtao ZhangDAC 2023 · 被引用 2 次
它引用的顶会 Paper5
- ZeroTrace : Oblivious Memory Primitives from Intel SGXSajin Sasy, Sergey Gorbunov, Christopher W. FletcherNDSS 2018 · 被引用 244 次
- OBLIVIATE: A Data Oblivious Filesystem for Intel SGXAdil Ahmad, Kyungtae Kim, Muhammad Ihsanulhaq Sarfaraz, Byoungyoung LeeNDSS 2018 · 被引用 144 次
- DeepSniffer: A DNN Model Extraction Framework Based on Learning Architectural HintsXing Hu, Ling Liang, Shuangchen Li, Lei Deng 等ASPLOS 2020 · 被引用 128 次
- TaoStore: Overcoming Asynchronicity in Oblivious Data StorageCetin Sahin, Victor Zakhary, Amr El Abbadi, Huijia Lin 等S&P 2016 · 被引用 98 次
- Multi-Range Supported Oblivious RAM for Efficient Block Data RetrievalYuezhi Che, Rujia WangHPCA 2020 · 被引用 16 次
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