Smart Campus Network To Detect Distributed Denial Of Service Attacks In Software Defined Networks
Abstract
Software Defined Networks is an emerging network architecture that control and manages the campus network automatically during the arrival of network traffic flows. Distributed Denial of Service attack is the unvanishable threat in all networking ecosystem. The proposed Smart Campus Network is deployed with supervised Random Forest and K Nearest Neighbor algorithm that self-learns the training data to detect and classify the type of attack traffic flows that reaches centralized controller. Smart Campus Networks automates to incorporate the network security policies for the incoming network traffic flows. In experimentation, the proposed method outperforms existing methods with respect to attack detection time, bandwidth utilization, average number of installed flow entries in a switch, flow arrival rate and packet delivery ratio.