Limits of Preprocessing for Single-Server PIR

G. Persiano, Kevin Yeo
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引用次数: 10

Abstract

We present a lower bound for the static cryptographic data structure problem of single-server private information retrieval (PIR) . PIR considers the setting where a server holds a database of n entries and a client wishes to privately retrieve the i -th entry without revealing the index i to the server. In our work, we focus on PIR with preprocessing where an r -bit hint may be computed in a preprocessing stage and stored by the server to be used to perform private queries in expected time t . We consider the public preprocessing setting of Beimel et al. [JoC, 2004] where the hint is publicly available to everyone including the adversary. We prove that for any single-server computationally secure PIR with preprocessing it must be that tr = Ω( n log n ) when r = Ω(log n ). If r = O (log n ), we show that t = Ω( n ). Our lower bound holds even when the scheme errs with probability 1 /n 2 and the adversary’s distinguishing advantage is 1 /n . Our work improves upon the tr = Ω( n ) lower bound of Beimel et al. [JoC, 2004]. We prove our lower bound in a variant of the cell probe model where only accesses to the memory are charged cost and computation and accesses to the hint are free. Our main technical contribution is a novel use of the cell sampling technique (also known as the incompressibility technique) used to obtain lower bounds on data structures. In previous works, this technique only leveraged the correctness guarantees to prove lower bounds even when used for cryptographic primitives. Our work combines the cell sampling technique with the privacy guarantees of PIR to construct a powerful, polynomial-time adversary that is critical to proving our higher lower bounds.
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单服务器PIR的预处理限制
给出了单服务器私有信息检索(PIR)静态密码数据结构问题的下界。PIR考虑这样一种设置:服务器持有一个包含n个条目的数据库,客户机希望私下检索第i个条目,而不向服务器透露索引i。在我们的工作中,我们关注带有预处理的PIR,其中一个r位提示可以在预处理阶段计算,并由服务器存储,用于在预期时间t内执行私有查询。我们考虑Beimel等人[JoC, 2004]的公开预处理设置,其中暗示对包括对手在内的所有人都是公开的。我们证明了对于任何具有预处理的单服务器计算安全PIR,当r = Ω(log n)时,tr = Ω(n log n)。如果r = O (log n)我们证明t = Ω(n)我们的下界即使在方案出错的概率为1 /n / 2且对手的显著优势为1 /n时也成立。我们的工作改进了Beimel等人的tr = Ω(n)下界[JoC, 2004]。我们在单元探测模型的一个变体中证明了我们的下界,其中只有访问内存是收费的,计算和访问提示是免费的。我们的主要技术贡献是对单元采样技术(也称为不可压缩技术)的新颖使用,用于获得数据结构的下界。在以前的工作中,该技术仅利用正确性保证来证明下界,即使在用于加密原语时也是如此。我们的工作将单元采样技术与PIR的隐私保证相结合,构建了一个强大的多项式时间对手,这对于证明我们的上下界至关重要。
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