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Algorithm for finding partitionings of hard variants of boolean satisfiability problem with application to inversion of some cryptographic functions

机译:查找布尔可满足性问题的硬变体分区的算法及其在某些密码函数求逆中的应用

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摘要

In this paper we propose an approach for constructing partitionings of hard variants of the Boolean satisfiability problem (SAT). Such partitionings can be used for solving corresponding SAT instances in parallel. For the same SAT instance one can construct different partitionings, each of them is a set of simplified versions of the original SAT instance. The effectiveness of an arbitrary partitioning is determined by the total time of solving of all SAT instances from it. We suggest the approach, based on the Monte Carlo method, for estimating time of processing of an arbitrary partitioning. With each partitioning we associate a point in the special finite search space. The estimation of effectiveness of the particular partitioning is the value of predictive function in the corresponding point of this space. The problem of search for an effective partitioning can be formulated as a problem of optimization of the predictive function. We use metaheuristic algorithms (simulated annealing and tabu search) to move from point to point in the search space. In our computational experiments we found partitionings for SAT instances encoding problems of inversion of some cryptographic functions. Several of these SAT instances with realistic predicted solving time were successfully solved on a computing cluster and in the volunteer computing project SAT@home. The solving time agrees well with estimations obtained by the proposed method.
机译:在本文中,我们提出了一种构建布尔可满足性问题(SAT)的硬变体分区的方法。这样的划分可以用于并行求解对应的SAT实例。对于相同的SAT实例,可以构造不同的分区,每个分区都是原始SAT实例的一组简化版本。任意分区的有效性取决于从中求解所有SAT实例的总时间。我们建议基于蒙特卡洛方法的方法,用于估计任意分区的处理时间。对于每个分区,我们在特殊的有限搜索空间中关联一个点。特定分区有效性的估计是该空间相应点的预测函数的值。寻找有效分区的问题可以表述为优化预测功能的问题。我们使用元启发式算法(模拟退火和禁忌搜索)在搜索空间中从一个点移动到另一个点。在我们的计算实验中,我们发现了SAT实例的分区,这些分区编码了一些密码函数的反演问题。这些具有实际预测解决时间的SAT实例中的几个实例已在计算集群和志愿者计算项目SAT @ home中成功解决。求解时间与所提出的方法获得的估计吻合得很好。

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