A Privacy-Preserving Mechanism Based on Privacy Situation Awareness for Information Sharing in OSNs

Various privacy-preserving mechanisms have been proposed to protect the privacy of individuals in online social networks, which have corresponding advantages in situations where they are primarily concerned. However, most of them applied static policies to all information audiences, resulting in the inability to satisfy the fine-grained requirements of information owners because audiences in the information propagation path are heterogeneous. To this end, we propose a novel privacy-preserving mechanism, in which the impact of each audience on the privacy situation of the information owner is evaluated. Particularly, to meet the subjective requirements of the information owner, the prospect theory is utilized to match the impact of the audience with the requirements of the owner, only the audience who satisfies the matching conditions can be authorized to receive the information. Furthermore, the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is leveraged to implement the proposed mechanism, and the use of CP-ABE can also prevent service providers from obtaining the information of individuals. Therefore, through our mechanism, the information owner could reduce the risk from individuals and service providers, while meeting its personalized requirements. The theoretical analysis and simulation experiment demonstrates that our mechanism has obvious advantages in controlling privacy risk and is compatible with various scenarios.