Modelling Shared Co-owned Data Flow in Online Social Networks by Formal Methods

Abstract

Online social networks are common platforms for people to make connections and communicate to others. People are given a virtual space to share data either including only their own ids or including other users' ids. Data sharing sometimes cause privacy issues in online social networks because of inclusion of other users' ids. Researchers have studied on the privacy issues and these online platforms have taken measurements to preserve privacy leakage because of its inclusion on data. Users are not only allowed to share a content of data but also re-share a shared content. Re-sharing has also caused privacy issues in online social network platforms. Recently, Facebook has made an update on shared contents, in which permissions have been restricted based on groups. However, it has not solved the main issue since the proposed solution is a coarse-grained control not a fine-grained control on shared contents of data. This work introduces a fine-grained control flow on shared contents in which users’ reputation and data sensitivity are used. To specify our proposed work's specifications and verify the proposed model, we used formal modelling. Formal analysis of this work is used to prove the applicability of the model and verification of the specifications.

Keywords

• Data Flow
• Data Sensitivity
• Event-B
• Formal Modelling
• Online Social Networks

References

1. Akkuzu, G., Aziz, B., & Adda, M. (2019, October). Advantages of havingusers’ trust and reputation values on data sharing process in online socialnetworks. In 2019 Sixth International Conference on Social Networks Anal-ysis, Management and Security (SNAMS) (pp. 189-195). IEEE.
2. Akkuzu, G., Aziz, B., & Adda, M. (2020). Towards consensus-based groupdecision making for co-owned data sharing in online social networks. IEEEAccess, 8, 91311-91325.