Year of Joining: 2017
Year of Completion: 2022
Email ID: email@example.com
Advisor: V. Sridhar
Research Interest: Privacy, Networked Privacy
Education / Work Experience: Masters in Technology in Computer Science (2017-2022)
Thesis Title: Modelling and Analysis of Multi-Party Privacy in Online Social Media Networks
Thesis abstract: In the past decade, participation and user disclosures in Online Social Networks (OSNs) have exponentially increased. As a consequence, the average user accumulates a diverse audience, with members belonging to the user’s different social groups being simultaneously present in the same space. To optimally navigate their audience, users end up having to make difficult disclosure decisions often leading to privacy violations caused by self-presentation and context collapse issues. The problem gets exacerbated in this case of multiparty content, where the privacy requirements of all the stakeholders need to be accounted for. Current mechanisms for online privacy do not address this issue on the required scale and therefore fall short of user requirements. To this end, the thesis studies multiparty privacy on OSNs to come up with a heuristic model. The model is then enveloped around a procedure which we claim to be socially responsible as it takes user interaction requirements as constraints. It also provides a proof of concept for the same by evaluating our heuristics against generated data.