摘要： 在MASK 算法基础上提出了基于多参数随机扰动后布尔规则的挖掘过程，通过对实验结果的评估分析，表明该算法能够提供较高的隐私保护，并讨论了隐私保护及挖掘精度之间的关系。最后对未来多参数随机扰动数据挖掘研究进行了展望。

关键词: 随机扰动；重构；频集

Abstract: This paper presents a process of boolean rule mining based on multi-factor random perturbation, and analyzes the consequent outcome that indicates the algorithm can provide stronger privacy protection. It discusses the relation of privacy preserving and data mining accuracy. Then, it covers an initial study on the future directions for multi-factor random perturbation in the area of data mining

Key words: Random perturbation; Reconstruction; Frequency itemsets