正在进行的工作:CAMiSE:内容可寻址内存集成的可搜索加密

Arnab Bag, Sikhar Patranabis, Debdeep Mukhopadhyay
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引用次数: 1

摘要

可搜索对称加密(SSE)旨在支持直接在加密数据库上高效执行查询。SSE的实际实现由于随机内存访问和计算密集型加密操作而受到性能瓶颈的影响。我们提出CAMISE -一个完全关联内存集成框架,用于设计具有大型数据库快速查询处理的SSE系统。我们展示了定制设计的内容可寻址内存(CAM)的一种新用法,以最大限度地减少SSE系统中查询执行期间的存储访问延迟。我们在这个框架内原型化了一个著名的SSE方案,即遗忘交叉标签(OXT)。与传统的基于软件的实现相比,我们的实现实现了5 -7倍的速度提升,同时平滑地扩展到具有数百万条记录的真实数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Work-in-Progress: CAMiSE: Content Addressable Memory-integrated Searchable Encryption
Searchable symmetric encryption (SSE) aims to support efficient query-execution directly over encrypted databases. Practical implementations of SSE suffer from performance bottlenecks due to randomised memory accesses and computation-intensive cryptographic operations. We propose CAMISE – a fully associative memory-integrated framework for designing SSE systems with fast query processing over large databases. We show a novel usage of custom-designed Content Addressable Memory (CAM) to minimise storage-access latencies during query execution in SSE systems. We prototype a well-known SSE scheme, namely Oblivious Cross Tags (OXT), within this framework. Our implementation achieves 5x-7x speed-up over traditional software-based implementations while scaling smoothly to real-world databases with millions of records.
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