OSN User Filtered Walls for Unwanted Messages Using Content Mining?

In today’s On-line Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning based soft classifier automatically labeling messages in support of content-based filtering. To study strategies and techniques limiting the inferences that a user can do on the enforced filtering rules with the aim of bypassing the filtering system by creating a instance randomly notifying a message system that should instead be blocked, or detecting modifications to profile attributes that have been made for the only purpose of defeating the filtering system. Automatically user will get a mail notification.