Survey of Filtering System For OSN (Online Social Networks)

In recent years, Online Social Networks (OSNs) have become an important part of daily life. Users build explicit networks to represent their social relationships. Users can upload and share information related to their personal lives. The potential privacy risks of such behaviour are often ignored. And the fundamental issue in today On-line Social Networks is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Today OSNs provide very little support to prevent unwanted messages on user walls. For that purpose, we proposed a new 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 (ML) based soft classifier automatically labelling messages in support of content-based filtering. The system exploits a ML soft classifier to enforce customizable content-dependent Filtering Rules. And the flexibility of the system in terms of filtering options is enhanced through the management of Blacklists. The proposed system gives security to the On-line Social Networks.