k-匿名隐私保护模型在隐私保护过程中会产生大量k-匿名数据.为研究k-匿名数据中的数据依赖问题,提出一种扩展函数依赖,将经典函数依赖中的被决定属性取值相等这个条件进行扩展,使其取值来自于同一个指定集合.应用结果表明,该扩展函数依赖不仅包括经典函数依赖、垂直函数依赖、水平函数依赖、度量函数依赖的特性,而且可以从数据完整性的角度描述k-匿名数据的约束条件及指导k-匿名隐私保护模型中准标识符的选取.%The widely use of the k-anonymity privacy protection model in the privacy protection field yields has a large number of k-anonymity data. For researching on the data dependency in k-anonymity data, this paper defines an Extended Functional Dependencies(EFDs), which extends the value of the right properties get from the certain set, instead of the equality in classic function dependencies. Application result shows that EFDs not only covers classic functional dependency, horizontal function dependencies, and metric functional dependencies, but also can describe the constraints of the k-anonymity data from perspective of data integrity and instruct the selection of quasi-identifier in k-anonymity privacy protection model.
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