Distributed detection of zero-day network traffic flows

Abstract

© Springer Nature Singapore Pte Ltd. 2018. Zero-day (or unknown) traffic brings about challenges for network security and management tasks, in terms of identifying the occurrence of those events in the network in an accurate and timely manner. In this paper, we propose a distributed mechanism to detect such unknown traffic in a timely manner. We compare our distributed scheme with a centralized system, where all the network flow data are used as a whole to perform the detection. We combined supervised and unsupervised learning mechanisms to discover and classify the unknown traffic efficiently, using clustering and Random Forest (RF) based schemes for this purpose. Further, we incorporated t..