The Use of K-NN and Bees Algorithm for Big Data Intrusion Detection System
Saqr Mohammed Almansob, Aqueel Ahmed Jalil, Santosh S. Lomte · IOSR Journal of Computer Engineering · 2017
Big data problem in intrusion detection system is mainly due to the large volume of the data.The dimension of the original data is 41.Some of the feature of original data are unnecessary.In this process, the volume of data has expanded into hundreds and thousands of gigabytes(GB) of information.The dimension span of data and volume can be reduced and the system is enhanced by using K-NN and BA.The reduction ratio of K-DD datasets and processing speed is very slow so the data has been reduced for extracting features by Bees Algorithm (AB) and use K-nearest neighbors as classification (KNN).So, the KDD99 datasets applied in the experiments with significant features.The results have gave higher detection and accuracy rate as well as reduced false positive rate.