University of North Carolina at Charlotte
In this paper, the authors focus on the specific problem of Big Data classification of network intrusion traffic. It discusses the system challenges presented by the big data problems associated with network intrusion prediction. The prediction of a possible intrusion attack in a network requires continuous collection of traffic data and learning of their characteristics on the fly. The continuous collection of traffic data by the network leads to big data problems that are caused by the volume, variety and velocity properties of big data.