Abstract
Individual privacy in social networks has become a major concern of late. In spite of adoption of various anonymisation techniques for user profiles, various attacks are possible. Each user needs to be anonymised depending on their sensitivity. Sensitivity can be measured by the relative importance of the user on the basis of degree centrality and prestige rank. This paper proposes various algorithms to automatically generalise the nodes for preserving privacy. Issues like information loss are also discussed.
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: International Journal of Computational 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.
