The (P, α, K) anonymity model for privacy protection of personal information in the social networks

Author

Kong Qing-jiang ; Wang Xiao-hao ; Zhang Jun

Author_Institution

Coll. of Comput. Sci. & Technol, Zhejiang Univ. of Technol., Hangzhou, China

Volume

2

fYear

2011

fDate

20-22 Aug. 2011

Firstpage

420

Lastpage

423

Abstract

The (P, α, K) anonymity model for privacy protection of personal information in the social networks is proposed in this paper. The hidden fields P and the hidden levels a are set according to the individual privacy needs of the users. Then make the released data to meet the privacy protection requirements through the Datafly algorithm and the clustering algorithm. The experimental data shows that the (P, α, K) model is better than the traditional K-anonymity model and L-Diversity modeling reducing the running time and reducing the loss of information.

Keywords

data privacy; pattern clustering; security of data; social networking (online); (P, α, K) anonymity model; L-diversity model; clustering algorithm; data fly algorithm; personal information; privacy protection; social networks; Clustering algorithms; Data models; Data privacy; Databases; Educational institutions; Privacy; Social network services; Personal Information; Personalized; Privacy Protection; Social Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International

Conference_Location

Chongqing

Print_ISBN

978-1-4244-8622-9

Type

conf

DOI

10.1109/ITAIC.2011.6030363

Filename

6030363