Open AccessHybrid and Decentralized Privacy Preservation using D-Anonymity and T-Closeness in Social Network
Author(s) -
Annapurna Kattimani,
Asst Professor,
C. B. Akki
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1109.1292s19
Subject(s) - anonymity , k anonymity , closeness , computer science , information privacy , social network (sociolinguistics) , privacy software , internet privacy , privacy by design , computer security , data mining , world wide web , social media , mathematics , mathematical analysis
Although Social Network (SN) knowledge is significant assets for data examination, freeing the data to the general public could reason an invasion of privacy. Privacy insurance is taken a lot of seriously than various data mining duties. The privacy problems are dealt with by several algorithms and strategies in the literature. But, perpetually there exists a trade-off between privacy and data.Our objective in this work is to design and develop a privacy-preserving solution for the social network. We have used K-anonymity and T-closeness algorithm and data anonymization. Further, data anonymization is decentralized by giving control of anonymization to the data owner. The solution is implemented on a dummy social network for testing the effectiveness of the privacy preservation solution proposed by us.