Insights into today’s cyber trends and threats : Meta and Base Classifier Models for Network Traffic Classification

Abstract

The interconnectivity between the computers that provide a single network with lots of advantages is termed as the network. A network is a scenario that allow to collect and connect a number of computers for exchanging the information and offering facilities to other resources. To detect malicious activities from the network various classification techniques are designed. The existing technique is SVM which is applied to classify data into malicious and normal classes. This research work designed a stacking technique in order to classify the network traffic. The base classifier which is used, is known as SVM and meta-classifier is KNN classifier. The proposed model is the hybrid for the network traffic classification. Python is employed to execute the designed technique and the metrics namely accuracy, precision and recall are considered to analyze the designed technique.