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MICRO2025顶会

SmartPIR: A Private Information Retrieval System using Computational Storage Devices

Zehao Chen, Honghui You, Qian Wei, Hang Lu, Lei Ju, Zhaoyan Shen

2025年份
4被引次数

摘要

Fully Homomorphic Encryption-based Private Information Retrieval systems provide strong privacy by enabling encrypted queries on databases hosted by untrusted servers.However, adoption is limited by system-level bottlenecks, including severe I/O constraints in large-scale settings and inefficiencies in handling variable-length data.To solve these issues, we present SmartPIR, a scalable PIR system that tackles these challenges through a protocol and architecture co-design.First, we introduce an in-storage computing framework that offloads FHE operations to computational storage devices (CSDs), eliminating the overhead of large-volume data movement.To address the limited computational capacity of CSDs, we further propose a zero-skipping encoding strategy at the protocol level, which decouples actual payloads from paddings to avoid redundant computations.Additionally, SmartPIR incorporates two key architectural optimizations: (1) a resource-efficient FPGA circuit design and (2) a load-aware scheduling strategy, which collectively sustain high throughput and ensure scalability.Implemented on a commercial off-the-shelf CSD array, SmartPIR achieves a 10 2 ×∼10 3 × speedup over state-of-the-art CPU-based PIR schemes.

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