International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1253 DETECTING ROOT OF THE RUMOR IN SOCIAL NETWORK USING GSSS S.NIVETHA 1 ,R.PRIYADHARSHINI 2 ,P.BALAKUMAR 3 ,R.K.KAPILAVANI 4 1 B.E,Department of Computer Science and Engineering, Prince Shri Venkateshwara Padmavathy Engineering College,Tamilnadu,India. 2 B.E,Department of Computer Science and Engineering, Prince Shri Venkateshwara Padmavathy Engineering College,Tamilnadu,India. 3 Professor ,Department of Computer Science and Engineering, Prince Dr.K.Vasudevan College of Engineering and Technology,Tamilnadu,India. 4 Assistant Professor ,Department of Computer Science and Engineering, Prince Dr.K.Vasudevan College of Engineering and Technology,Tamilnadu,India. ------------------------------------------------------------------***--------------------------------------------------------------- ABSTRACT Detecting source of the rumor in social network plays a role in limiting the damage caused by them. However rumor spreading in social network to a shorter distance only can be identified by using some of the methodologies. In this paper, we introduce a concept to detect root of the rumor that spread in the social network in wider range by using two concepts. First, we make use of monitor nodes in order to record the data and report it to the server. Second, Greedy Source Set Size (GSSS) Algorithm to find the exact solution and also improve the efficiency for the problem. The root of the rumour is identified by three methodologies and they are Identification method, Reverse dissemination method and microscopic rumor spreading model. The identification method reduces time varying network into series of static network and reverse dissemination method resolve the set of suspect and finally microscopic method establish the real root of rumor by calculating maximum likelihood(ML) value for each suspect. The experiment result shows that it can reduce 80-95% of the root of the rumor in social networks in dynamic time varying network topology. Keyword:- Monitor nodes, rumor spreading, GSSS, source identification, and maximum likelihood . 1.INTRODUCTION )n today’s world, internet has become the most important medium to circulate information. Social networks are an interesting class of graphs likely to become an increasing importance in the future times [1]. Rumor spreading in social networks plays a critical role in our society and is one of the basic mechanisms for the information dissemination in the networks [2] .For instance, in October 2011, a rumor message in social network that "Apple CEO had heart attack". When the word hit the internet, in first hour of trading the stock lost 10% of its values, spurred by panicked investor who believe that entire job is done by Steve Jobs. The ubiquity and speed access not only improve efficiency of social media but also main reason for rapid spreading of rumor about different communities [3].The solution to this problem are applied in many applications such as identifying the source of infectious disease and finding the source of leaked confidential information.2 1.1 PREDICTION OF RUMOR The identification of rumor message in social network is the most preliminary basis to detect the root of rumor. Existing works mainly detected rumor by analyzing only shallow features of messages. In many scenarios, it is not satisfactory in differentiating rumor message from normal message. But then several methods used a combination of shallow features and implicit features of messages in order to identify the rumor message with efficiency[9].Three methods are mainly consider in detecting the rumor that comprise of profile based, information based and traverse based. 1.2 RELATED WORKS Nowadays, social networks has been incorporated with several communities in sharing malicious information such as computer virus and rumors cause damage to our society[4],[5]. Development of mobile devices had created a great effect in spreading of dynamic information in social