Security and scalability issues in big data analytics in heterogeneous networks

Big data is most widely used in many applications to overcome the issues in various domains. The processing of huge and complicated data becomes more complicated by using various traditional algorithms or techniques. In big data there are two issues privacy and security are discussed. One of the important challenges in this is to overcome the issues occur in the preventing the attacks on data by the unauthorized persons. Big Data is the collection of huge data from the various sources and which is interrelated data is present and the data needs its own security from unauthorized access. Previously various algorithms are used for processing of huge datasets but the result is not that much of accurate. In this paper, An Ensemble big data analytics algorithm (EBDAA) for various types of attacks detection is implemented. The KDD Cup 99 dataset is utilized in this paper with the proposed algorithm. The results show the performance of EBDA.