117598.pdf (7.76 MB)
Scoring users’ privacy disclosure across multiple online social networks
journal contribution
posted on 2023-05-19, 06:09 authored by Aghasian, E, Saurabh GargSaurabh Garg, Gao, L, Yu, S, Erin MontgomeryErin MontgomeryUsers in online social networking sites unknowingly disclose their sensitive information that aggravate the social and financial risks. Hence, to prevent the information loss and privacy exposure, users need find ways to quantify their privacy level based on their online social network data. Current studies that focus on measuring the privacy risk and disclosure, consider only a single source of data, neglecting the fact that users in general can have multiple social network accounts disclosing different sensitive information. In this paper, we investigate an approach that can help social media users to measure their Privacy Disclosure Score (PDS) based on information shared across multiple social networking sites. In particular, we identify the main factors that have impact on users privacy, namely, sensitivity and visibility, to obtain the final disclosure score for each user. By applying the statistical and fuzzy systems, we can specify the potential information loss for a user by using obtained PDS. Our evaluation results with real social media data show that our method can provide a better estimation of privacy disclosure score for users having presence in multiple online social networks.
History
Publication title
IEEE AccessVolume
5Pagination
13118-13130ISSN
2169-3536Department/School
School of Information and Communication TechnologyPublisher
Institute of Electrical and Electronics EngineersPlace of publication
United StatesRights statement
Copyright 2017 IEEE.Repository Status
- Open