Title :
Personalized-Granular k-Anonymity
Author :
Shen, Yanguang ; Liu, Yonghong ; Zhang, Yanli
Author_Institution :
Coll. of Inf. & Electron. Eng., Hebei Univ. of Eng., Handan, China
Abstract :
We propose a new anonymity method, which is called Personalized-Granular_k-anonymity. In view of the difference of selectivity of decision-making based on personalized granularity of privacy preserving, we propose a k-anonymity method based on personalized granularity for the first time. Then different space can be separated according to granularity of personalized decision to meet the different demands of privacy preserving. The heuristic algorithms and the correlative definitions are also given in this paper. It has been theoretically proved that the new method can protect privacy preservation with more reasonable personalization and higher accuracy.
Keywords :
data encapsulation; data privacy; decision making; Personalized-Granular_k-anonymity; decision making; privacy preservation; Data privacy; Decision making; Educational institutions; Fuzzy set theory; Heuristic algorithms; Humans; Mathematics; Protection; Resists; Set theory;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5365939