A trust based approach for protecting user data in social networks

This work introduces a novel social access control (SAC) strategy inspired by multi-level security (MLS) for protecting data on social networks and describes one aspect of the SAC model that supports the confidentiality of read-only data objects.

Abstract

Social networks are graphs that represent relations among people, institutions, and their activities. We introduce a novel social access control (SAC) strategy inspired by multi-level security (MLS) [1] for protecting data on social networks. In MLS, the data objects and subjects are classified in hierarchical levels based on security clearance and access controlled accordingly. Instead of clearance levels, we use trust levels to annotate objects and subjects. The trust level of an object is specified by the creator. The trust level of a subject is obtained from a trust modeling process [2, 3]. Reading a data object is controlled using the relative trust values of subjects and objects. We describe one aspect of the SAC model that supports the confidentiality of read-only data objects. We performed simulation studies using traces from the flickr.com social network to evaluate the performance of some key primitives used in the SAC design.