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Monitoring Network Traffic Based on Mapreduce in Simplified Data Processing Using Intrusion Detection System

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Abstract
Big data is having more key roles as infrastructure information e-pay and e-business social media in Internet booming due to the user conveniences and user benefits. Now a day Internet security problems is most of challenges for some security session. The privacy and security should be Reinforce via secured cloud computing and hadoop server. It Refer a comprehend security solution for attack detection and attack prevention. In this article research distributed clustering scheme and propose a cluster- based routing protocol for Delay Tolerant hadoop Networks (DTHNs). Due to the lack of continuously communicate among hadoop network nodes and possibility of error to estimate the nodal contact probability convergent and stability is become a major challenge in distributed clustering network. The basic idea is distributed group of hadoop nodes with quasi mobility pattern into a clusters, It can be interchanged data without overhead and load balancing then it also achieve scalable and efficient routing via distributed hadoop server .To detect and prevent the data from attacker. An exponentially weighted average moving time (EWAM) schema is worked for online update with nodal contact probabilities, which means prove the converge to true contact probability and it carried out to evaluate the efficiency and effectiveness of cluster based routing protocol.
Keywords:Big data, cloud computing, delay Tolerant hadoop Networks, distributed clustering, privacy and security

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