One of the most essential issue in today’s Online Social Networks (OSNs) is to provide users the ability to have full control on the messages which are showed on their own secretive space to avoid that unwanted content is which is being displayed. Till the date, OSNs provide little support to this requirement. To fill the gap, we suggest a system that permitting all the OSN users to have a direct access control on the messages displayed on their walls in social networks. Spamming remains parsimoniously feasible because promoters have no operating costs beyond the management of their mailing lists, and it is difficult to hold senders responsible for their mass mailings. Because the barrier to entry is so low, spammers are numerous, and the volume of unsolicited mail has become very high. 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.