FILTER UNWANTED MESSAGES FROM WALLS AND BLOCKING NON-LEGITIMATE USERS IN OSN

In recent years, on-line Social Networks (OSNs) became a crucial part of daily life. Users build particular networks to represent their social relationships. Users are able to upload and share information associated to their personal lives. The privacy risks of such behaviour are typically unnoticed. Nowadays OSNs give little or no support to stop unwanted messages on user walls. For that purpose, a new system is designed to permit OSN users to have a direct control on the messages posted on their walls. This can be achieved through a flexible rule based system, that allows users to customise the filtering criteria to be applied to their walls, and a Machine Learning (ML) primarily based soft classifier mechanically labelling messages in support of content based filtering. The system make use of a ML soft classifier to enforce customizable content-dependent Filtering Rules (FRs). And also the flexibility of the system in terms of filtering choices is increased through the management of Blacklists. Filtered wall is a system to filter undesired messages from OSN walls. This system approach decides when user should be inserted into a black list. The proposed system offers security to the On-line Social Networks.