Enabling Security Service Using Content Based Message Filtering System on OSN Userwalls

Abstract

At the present day,Online Social Networks gains more and more popularity , since it provides the most easiest interactive medium to share the informations among the group of users.However,it provides a little support to control the messages that are posted on their own private user walls.In this paper,an automated information filtering system is proposed that can filter the posted messages based on the filtering criteria.It allows OSN users to customize the filtering criteria on the messages and also the undesired users might be banned from a wall for the specified time period.The proposed approach uses two level text analysis algorithm.In the first level,posted messages are classified using the improved text classification algorithm and the messages are labeled.The second level filter the message based on the Filtering Rules(FR) that are stated by the user wall.Finally,the undesired messages that are posted by the group user more than the threshold value can be placed in the BlackList based on the BlackList(BL) rule which is also customized by the user wall.The BL users can be banned for the specified time period from the user wall.Besides,the efficiency of our approach is manifested by the preliminary experiment.