在保留引用局部性的同时,对程序进行有限的遗忘执行的数据结构

A. Varadarajan, R. Venkatesan, C. Rangan
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引用次数: 1

摘要

介绍了一种有限遗忘执行模型下程序执行的数据结构。为了按照Goldreich和Ostrovsky[2]的思路进行完全遗忘执行,基于一些加密假设和安全硬件的存在,将给定的程序转换为具有完全随机执行的程序。完全随机的内存访问模式不尊重程序中引用的局部性,而这通常是程序的效率所在。我们提出了一个限制遗忘的模型,从而使程序能够有效地执行;在这里,攻击者标记了一个变量,并试图生成一个候选位置列表,在执行$T$之后,该变量可能被存储在这些位置。我们提出了一种基于扩展树的随机化算法,并证明了这种列表的下界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data structures for limited oblivious execution of programs while preserving locality of reference
We introduce a data structure for program execution under a limited oblivious execution model. For fully oblivious execution along the lines of Goldreich and Ostrovsky [2], one transforms a given program into a one that has totally random looking execution, based on some cryptographic assumptions and the existence of secure hardware. Totally random memory access patterns do not respect the locality of reference in programs to which the programs generally owe their efficiency. We propose a model that limits the obliviousness so as to enable efficient execution of the program; here the adversary marks a variable and tries to produce a list of candidate locations where it may be stored in after $T$-steps ofexecution. We propose a randomized algorithm based on splay trees,and prove a lower bound on such lists.
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