Combining intrusion detection datasets using MapReduce
Mondher Essid, Farah Jemili · 2016
Extensive use of computer network and huge amount of data had led several works to focus on intrusion detection system, which are based on single dataset or to combine multiple detection techniques to analyze detection rate and false positive flag. This paper presents a new way to combine intrusion detection dataset, we will concentrate about KDD99, DARPA dataset using bigdata technique (mapreduce). One main goal is to generate single dataset with different attack type that is realistic and meets real world criteria. Another major goal is to generate low false flag and higher detection rate. This work consists in combining dataset and removing redundancy information using Bigdata technique, in final step we will implement NaiveBayes network and K2 algorithm using WEKA Tools to analyze the dataset.