Paper Title
Detecting And Analyzing Ddos Attack Using Map Reduce In Hadoop

An assault on a network that floods it with so many requests that regular traffic is either slowed or completely interrupted. Unlike a virus or worm, this can cause severe damage to databases. A Distributed Denial of service (DDos) attack can employ hundreds or even thousands of computers that have been previously flooded by HTTP GET packet. The massive amounts of data that collect over time which difficult to analyze using common database management tools. Big data includes activity logs (machine generated data) which consist of unstructured format capture from web. The storage industry is continuously challenged as Big data increases exponentially where security is one of the challenging and harmful concern. To handle Big data Hadoop technology takes cardinal part in analysis. In this paper we have proposed detection of DDos attack by using Counter based algorithm and Access Pattern algorithm which will implemented in Hadoop framework. Along this we can provide future prediction functionality using analytics. Dashboard provides visual view which will help to unveil the attacker and loyal user along with statistics.