An OpenFlow-based collaborative intrusion prevention system for cloud networking

Abstract

Software-Defined Networking (SDN) is an emerging architecture that is ideal for today's high-bandwidth, dynamic network environments. In this architecture, the control and data planes are decoupled from each other. Although much research has been performed into how SDN can resolve some of the most-glaring security issues of traditional networking, less research has addressed cloud security threats, and, in particular, botnet/malware detection and in-cloud attacks. This work proposes an intrusion prevention system for cloud networking with SDN solutions. To realize collaborative defense, mechanisms of botnet/malware blocking, scan filtering and honeypot are implemented. Malicious traffic is isolated because bot-infected VMs are removed effectively and efficiently from the private cloud. The scanning behavior can be filtered at a very early stage of prevention, making the VMs less exploitable. A honeypot mechanism is also deployed to trap attackers. Experimental results show the high detection rate, high prevention accuracy and low vulnerability of the proposed system.