IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 599 RULE BASED MESSEGE FILTERING AND BLACKLIST MANAGEMENT FOR ONLINE SOCIAL NETWORK V.Ezhilvani 1 , K.Malathi 2 , R.Nedunchelian 3 1 Department of Computer Science and Engineering, Saveetha University, Chennai, India 2 Department of Computer Science and Engineering, Saveetha University, Chennai, India 3 Department of Computer Science and Engineering, Saveetha University, Chennai, India Abstract Online social network which play a most imperative role in today’s world, but the major issue in online social network is displaying undesirable content in user walls. Main involvement of this paper is to propose an automated system to automatically filter the undesirable messages for online social network user walls using content based filtering .so, that the user can able to control directly the message which has been posted on their walls. In content based filtering the information item is been selected based on correlation between the content of the item and the user preferences. Keywords: Social network, machine learning techniques, blacklist management --------------------------------------------------------------------***------------------------------------------------------------------ 1. INTRODUCTION Today online social network become most popular interactive medium to communicate with people and, share considerable amount of information and also gaining new friends over the internet. More than 300 social networking sites have common features in existence. The basic feature of social network is the ability to create and share a personal profile. This profile page includes a photo, and some basic personal information such as name, age, sex, location. Most of the social networks on the Internet also let you post videos, photos, and personal blogs on your profile page. One of the most important features of online social networks is to find and make friends with other site members. These friends also appear as links, so visitors can easily browse your online friend network. According to face book statistics 1million link, 2millon friends are requested, 3million messages have been send for every 20 minutes on face book. The content present in social network is constituted by short text, and the notable example is the messages written by Online Social Network users on particular private or public areas, known as general walls. Proposing an automated system, to filter undesired comments from online social network is the aim of the present work. This is named as, Filtered Wall (FW).In previous work the wall owner does not have the control of their own private area and this shows there is no content based preferences. Therefore it is not possible to prevent unwanted messages such as political or vulgar once. To fill this gap, In proposed system ,user specify what are the contents not to be displayed on his or her walls by providing certain set of filtering rules .Thus, the present idea support content based preferences ,that is the user have the direct control of their walls. This is can be done using Machine Learning (ML) text categorization procedure .And, this ML have the capability to automatically assign with each messages as a set of categories based on contents. And, also using the blacklist management to control the message posted on user walls 2. PROBLEM DEFINITION Today most of the people splurge more time in social network sites such as Face book, twitter, LinkedIn, Google plus etc…And the major issue in social network is user does not have a control over their walls because it does not support content based preferences .Therefore it is not possible to prevent undesired messages such as political or vulgar ones which is posted on the private space of the users. Likewise, huge volumes of data are extracted and posted to the social sites, so it becomes a sophisticated task to social network management. Most of the proposal is mainly focus on providing a classification mechanism to avoid useless data. 3. PROPOSED SYSTEM The main focus of this paper is to develop a system for online social network user to prevent unwanted messages based on content given by the user. And, also using the machine learning system to provide the flexible way to control the incoming messages. Enforce blacklist rule to avoid unwanted messages from unauthorized users to keep the wall secure. The three layer architecture in the below fig 1.In this three layer, first layer shows the social network manager, second layer shows the social network application and finally graphical user interface.