随机正交变换法在隐私保持关联规则挖掘中的应用

隐私保护是当前数据挖掘领域中一个十分重要的研究方向。本文针对关联规则挖掘中如何保持隐私的问题,采用一种不依赖具体数据的随机正交变换方法,从而解决了在数据集容量很大的情况下,运算量大的问题,并使用传统隐私保护度评价方法与正交变换的方向隐私保护度相结合的方法评价变换的隐私保护度,进而使得结果更符合实际情况。理论分析和论证表明本文中的方法具有很好的隐私性、高效性和适用性。

The Application of Random Orthogonal Transformations in Privacy Preserving Association Rules Mining

Privacy preserving is an important direction for data mining research.This paper is concentrated on the issue of protesting the underlying attribute values when sharing data for association rules mining,adopts a random orthogonal transformation method without depending on any concrete data and thereby solve the computational problems when handling large data sets.And then evaluates the privacy preserving degree of the random orthogonal transformation using the combination of the traditional evaluation metho...