ABSTRACT

Network security is important aspect in today’s world, as number for internet users are increasing rapidly. Security for these devices could be provided by software tool Intrusion Detection System (IDS) which monitors and analyze the network traffic. There are different machine learning approaches to design IDS which varies with accuracy, execution time and false alarm rate. This paper presents multi-core architecture on K-Nearest Neighbor (KNN) algorithms using python language. The experiments of the IDS are performed with KDD99 dataset. Evaluation results show that computational time decreased with exploitation of multicore architecture. So, this approach can be implemented for resource constrained Internet of Things.