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FOCES: Detecting Forwarding Anomalies in Software Defined Networks

Authors :
Chengchen Hu
Huanzhao Wang
Peng Zhang
Zuoru Yang
Shimin Xu
Hao Li
Qi Li
Source :
ICDCS
Publication Year :
2018
Publisher :
IEEE, 2018.

Abstract

A crucial requirement for Software Defined Network (SDN) is that data plane forwarding behaviors should always agree with control plane policies. Such requirement cannot be met when there are forwarding anomalies, where packets deviate from the paths specified by the controller. Most anomaly detection methods for SDN install dedicated rules to collect statistics of each flow, and check whether the statistics conform to the flow conservation principle. Such per-flow detection methods have a limited detection scope: they look at one flow each time, thus can only check a limited number of flows simultaneously. In addition, dedicated rules for statistics collection can impose a large overhead on flow tables of SDN switches. To this end, this paper presents FOCES, a network-wide forwarding anomaly detection method in SDN. Different from previous methods, FOCES applies a new kind of flow conservation principle at network wide, and can check forwarding behaviors of all flows in the network simultaneously, without installing any dedicated rules. Experiments show FOCES can achieve a detection precision higher than 90% for four network topologies, even when packet loss rates are as high as 10%.

Details

Database :
OpenAIRE
Journal :
2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)
Accession number :
edsair.doi...........c02cea0b1b4490449fc5eeab9dc7794b