Abstract
Privacy protection of Social Network becomes a more and more serious concern in applications. The common way to protect privacy is to use k-anonymity in data publishing of social network. In this paper, we study the theory of k-anonymity of social network, use weighted lower triangular matrix to represent the relationship among the nodes of social network, and propose a personalized a (d, k)-anonymity mode. The a (d, k)-anonymity algorithm experiments prove that it can make anonymous nodes of social network effectively resist d-neighborhood attack, and structure attack, at the same time, make the node information availability according to the personalized weight parameter a. The algorithm is usable, effective and efficient comparing with traditional (d, k)-anonymity algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: DEStech Transactions on Computer Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
