Real-time DDoS Attack Detection for Cisco IOS using NetFlow

Abstract

Flow-based DDoS attack detection is typically performed by analysis applications that are installed on or close to a flow collector. Although this approach allows for easy deployment, it makes detection far from real-time and susceptible to DDoS attacks for the following reasons. First, the fact that the flow export process is timeout-based and that flow collectors typically provide data to analysis applications in chunks, can result in detection delays in the order of several minutes. Second, by the nature of flow export, attack traffic may be amplified by the flow export process if the original packets are small enough and are part of small flows. We have shown in a previous work how to perform DDoS attack detection on a flow exporter instead of a flow collector, i.e., close to the data source and in a real-time fashion, which however required access to a fully-extendible flow monitoring infrastructure. In this work, we investigate whether it is possible to operate the same detection system on a widely deployed networking platform: Cisco IOS. Since our ultimate goal is to identify besides the presence of an attack also attackers and targets, we rely on NetFlow. In this context, we present our DDoS attack detection prototype that has shown to generate a constant load on the underlying platform — even under attacks — underlining that DDoS attack detection can be performed on a Cisco Catalyst 6500 in production networks, if enough spare capacity is available.

Publication
14th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2015)