Towards Real-Time Intrusion Detection for NetFlow and IPFIX

Towards Real-Time Intrusion Detection for NetFlow and IPFIX

Stať ve sborníku v databázi WoS či Scopus

DDoS attacks bring serious economic and technical damage to networks and enterprises. Timely detection and mitigation are therefore of great importance. However, when flow monitoring systems are used for intrusion detection, as it is often the case in campus, enterprise and backbone networks, timely data analysis is constrained by the architecture of NetFlow and IPFIX. In their current architecture, the analysis is performed after certain timeouts, which generally delays the intrusion detection for several minutes. This paper presents a functional extension for both NetFlow and IPFIX flow exporters, to allow for timely intrusion detection and mitigation of large flooding attacks. The contribution of this paper is threefold. First, we integrate a lightweight intrusion detection module into a flow exporter, which moves detection closer to the traffic observation point. Second, our approach mitigates attacks in near real-time by instructing firewalls to filter malicious traffic. Third, we filter flow data of malicious traffic to prevent flow collectors from overload. We validate our approach by means of a prototype that has been deployed on a backbone link of the Czech national research and education network CESNET.

DDoS attacks bring serious economic and technical damage to networks and enterprises. Timely detection and mitigation are therefore of great importance. However, when flow monitoring systems are used for intrusion detection, as it is often the case in campus, enterprise and backbone networks, timely data analysis is constrained by the architecture of NetFlow and IPFIX. In their current architecture, the analysis is performed after certain timeouts, which generally delays the intrusion detection for several minutes. This paper presents a functional extension for both NetFlow and IPFIX flow exporters, to allow for timely intrusion detection and mitigation of large flooding attacks. The contribution of this paper is threefold. First, we integrate a lightweight intrusion detection module into a flow exporter, which moves detection closer to the traffic observation point. Second, our approach mitigates attacks in near real-time by instructing firewalls to filter malicious traffic. Third, we filter flow data of malicious traffic to prevent flow collectors from overload. We validate our approach by means of a prototype that has been deployed on a backbone link of the Czech national research and education network CESNET.

Internet measurements, Denial of service, Intrusion
detection, NetFlow, IPFIX, Flow monitoring

Internet measurements, Denial of service, Intrusion
detection, NetFlow, IPFIX, Flow monitoring

HOFSTEDE, R.; BARTOŠ, V.; SPEROTTO, A.; PRAS, A.

2014

14.10.2013

International Federation for Information Processing

Zürich

978-3-901882-53-1

Proceedings of the 9th International Conference on Network and Service Management

1

6

6

http://www.cnsm-conf.org/2013/documents/papers/CNSM/p227-hofstede.pdf

cnsm13_realtime_intrusion_detection