Title :
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
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;
Conference_Titel :
Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-8622-9
DOI :
10.1109/ITAIC.2011.6030363
