A Bi-Fold Trust Model for Cooperative Privacy and Security Management in Online Social Media

A Bi-Fold Trust Model for Cooperative Privacy and Security Management in Online Social Media

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© 2023 by IJETT Journal
Volume-71 Issue-7
Year of Publication : 2023
Author : A. Satish Kumar, S. Revathy
DOI : 10.14445/22315381/IJETT-V71I7P202

How to Cite?

A. Satish Kumar, S. Revathy, "A Bi-Fold Trust Model for Cooperative Privacy and Security Management in Online Social Media," International Journal of Engineering Trends and Technology, vol. 71, no. 7, pp. 15-27, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I7P202

Abstract
The most significant platforms for people to engage with others are now Online Social Networks (OSNs) such as Facebook, Google, and Twitter. Text messages, videos, and photos describing users' daily lives are posted by tens of thousands to millions of people on OSNs. Sensitive information about users is frequently discovered in such data. If unauthorised parties can access data, the user's privacy is at risk. The trust-based mechanism's threshold in this study is established at a value that guarantees the user receives a significant long-turn return. This value is calculated by the difference between the benefit of uploading data and users' privacy risks. To address the lack of trust and lack of collaboration that is comparable to peer-to-peer systems. By adjusting the proposed mechanism's parameter, users can choose between sharing data and protecting their privacy. In this paper, Thompson Sampling (TS) Algorithm is used to solve the Multi-armed Bandit (MAB) problem formulation of the parameter selection problem. The weighting of user opinions is determined by their trust values, upgraded as privacy is violated. In this research work, the trust score of the users is computed via a new bifold trust model. The publisher must thus change the threshold to strike a balance between privacy protection and document sharing, and trust-based integration of trust values into the document anonymisation process may help to minimise the loss of user privacy. Simulations demonstrate that a trust-based approach ensures user trust by protecting privacy and minimising information loss in the system, intended to be implemented in the PYTHON working environment.

Keywords
Online social networks, Thompson Sampling (TS) Algorithm, Multi-Armed Bandit (MAB), Bifold trust model.

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