Destination-aware Adaptive Traffic Flow Rule Aggregation in Software-Defined Networks

no code implementations • 7 Sep 2019 • Trung V. Phan, Mehrdad Hajizadeh, Nguyen Tuan Khai, Thomas Bauschert

This method adapts the number of flow table entries in SDN switches according to the level of detail of traffic flow information that other mechanisms (e. g. for traffic engineering, traffic monitoring, intrusion detection) require.

Intrusion Detection

Q-DATA: Enhanced Traffic Flow Monitoring in Software-Defined Networks applying Q-learning

no code implementations • 4 Sep 2019 • Trung V. Phan, Syed Tasnimul Islam, Tri Gia Nguyen, Thomas Bauschert

We first describe and analyse an SDN-based traffic flow matching control system that applies a reinforcement learning approach based on Q-learning algorithm in order to maximize the traffic flow granularity.

Management Q-Learning +2

Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework

no code implementations • 27 Jul 2019 • Trung V. Phan, T M Rayhan Gias, Syed Tasnimul Islam, Truong Thu Huong, Nguyen Huu Thanh, Thomas Bauschert

We first analyze the adversary model of stealthy DoS attacks, the related vulnerabilities in SDN-based networks and the key characteristics of stealthy DoS attacks.

Anomaly Detection BIG-bench Machine Learning +2