Identifying DoS attacks on software defined networks: A relation context approach

Abstract

The recent emerge of Software Defined Networking (SDN) promotes both supporters and opponents to further explore this network architecture. One of the main attributes that characterize SDN is the significant role of software to manage and control the architecture. There are four major concerns for such software dominant role, security, performance, reliability, and fault tolerance. Among them security is considered a major concern. SDNs security concerns include attacks on the control plane layer such as DoS attacks. This paper presents an inference-relation context based technique for the detection of DoS attacks on SDNs. The proposed technique utilizes contextual similarity with existing attack patterns to identify DoS in an OpenFlow infrastructure. A validation of the proposed technique has been performed using a several benchmark datasets yielding promising results.