Collusion-resistant multiparty data sharing in social networks
Document Type
Article
Publication Title
International Journal of Electrical and Computer Engineering
Abstract
The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy risk and sharing loss to identify and resolve conflicts. In addition to conflict resolution, bot detection is also done to mitigate collusion attacks. The final decision to share the data item is then ascertained based on whether it passes the threshold condition for the above metrics.
First Page
1996
Last Page
2013
DOI
10.11591/ijece.v14i2.pp1996-2013
Publication Date
4-1-2024
Recommended Citation
Shetty, Nisha P.; Muniyal, Balachandra; Proothi, Nandini; and Gopal, Bhavya, "Collusion-resistant multiparty data sharing in social networks" (2024). Open Access archive. 6711.
https://impressions.manipal.edu/open-access-archive/6711