CS SEMINAR:On Privacy Scoring over Online Social Networks
Guest: Dr.Ali İnan
Title: Analysing User Behaviour and Assisting Users in Ever Advancing Technology
Date: January 17, 2024 14:30
Location: FENS G035 (physical only)
Abstract: Privacy scoring aims at measuring the privacy violation risk of a user over an online social network (OSN) based on attribute values shared in the user’s OSN profile page and the user’s position in the network. Existing studies on privacy scoring rely on possibly biased or emotional survey data. In this talk, we motivate working with real-world data collected from the professional LinkedIn OSN and show that probabilistic scoring models derived from the item response theory fit real-world data better than naive approaches. We also introduce the granularity of the data an OSN user shares on her profile as a latent dimension of the OSN privacy scoring problem. Incorporating data granularity into our model, we build the most comprehensive solution to the OSN privacy scoring problem. Extensive experimental evaluation of various scoring models indicates the effectiveness of this solution.
Bio: Ali İnan received the BS and MS degrees in computer science from Sabancı University, and the PhD degree in computer science from the University of Texas, Dallas. He is an associate professor in the Computer Engineering Department, Adana Alparslan Türkeş Science and Technology University. His research interests include database systems, data mining and security, and privacy issues related to the management of data. He is particularly interested in privacy preserving data mining.