QCS:一种OLAP预防多维推理方法的研究

摘要

针对目前多数联机分析处理(OLAP)推理控制方法计算复杂性高、实用性不强的问题,在前人研究基础上,提出一种改进的基于查询单元集QCS(Query Cells Set)的OLAP预防多维推理方法.该方法把OLAP查询的多维推理威胁预防检测放在查询涉及到的底层不相交的单元集(即QCS),而不是单个单元上,从而降低了推理威胁检测算法的计算复杂性,这更符合OLAP的查询处理要求.同时给出QCS方法的有效性证明和算法的实现,并用实例进行说明.与以往的推理控制方法相比,QCS方法不仅可有效保护OLAP系统的隐私信息,而且具有较高的计算效率,能满足OLAP系统的实用性要求.%For high complexity and low practicability of most on-line analytical processing (OLAP) system inference control approaches, the paper proposed an improved preventing multi-dimensional inference approach on the basis of previous researches. This approach is based on the QCS( Query Cells Set). It puts preventing detection of multi-dimensional inference threat on the cells set(not simple cell) that requested cells of the query depend on, so the complexity of detection algorithm is reduced greatly, which meets the normal query processing requirement of OLAP. Then the effectiveness proof and algorithm were provided,and an example was used to illustrate the algorithm as well. Compared with former inference control approaches,QCS approach not only protects the sensitive data in OLAP system effectively,but also has better computationally efficiency,which meets the practical requirements of OLAP system.