K-anonymity Algorithms Based on Multi-Dimensional Generalization Path
Jiao Liu · Jisuanji gongcheng · 2009
Microdata publication need satisfy the basic K-anonymity requirement as well as improve the precision of anonymized data.This paper proposes two related K-anonymity algorithms based on the notion of multi-dimensional generalization path,namely K-anonymity Filter algorithm and K-anonymity partial Filter algorithm.In comparison with classic Datafly algorithm and Incognito algorithm,the two algorithms offer more efficiency for both reducing anonymization cost and improving data precision.