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Fast and Secure Private Friend Recommendations in Online Social Networks
Raiyan Hossain defends their thesis for their MS in Cybersecurity. Watch the presentation on Zoom.
Abstract
Online Social Networks have completely transformed communication in the world of social networks. Participation in online social networks have been growing significantly and is expected to continue to grow in the upcoming years. As user participation in online social media is on the rise, so is the concern pertaining to user privacy and information security; users want to interact on social media without jeopardizing their privacy and personal information. Extensive research has been conducted in the area of developing privacy-preserving protocols to allow users to interact in a secure and privacy-preserving environment. One of the elements that social media have is the feature or ability to befriend other users. While a user may manually search for friends to "add", social media networks like Twitter, Facebook, Instagram, Snapchat and others facilitate friend recommendations to their users based on different criteria. We examine and compare the advantages and disadvantages of existing privacy-preserving techniques and proximity measurement metrics before incorporating them into our protocol. This these also scrutinized the security weaknesses and vulnerabilities of three Friend Recommendation Protocols from existing work and develop a corresponding solution. We propose a Faster and Secure Friend Recommendation (FSFR) protocol that is based on Shamir's Secret Sharing in Online Social Networks. The protocol facilitates friend recommendations in Online Social Networks in a fast, secure and private manner. Our FSFR protocol proves to be more efficient and secure compared to other existing protocols.
Committee Members