A Vulnerability Detection Method for SDN with Optimized Fuzzing

Abstract

In response to the rapid development of the big data era, the concept of Software Defined Networking (SDN) has been introduced and is gradually being applied to business. However, while this new network architecture is flexible enough to handle network data requirements. It is also inherently exposed to a wide range of security threats. In this paper, we propose an intelligent variation strategy to improve the detection efficiency and scope of SDN vulnerability scenarios based on an optimized fuzzing method. It performs vulnerability detection on SDN and prevents possible hazards more effectively. Based on the experimental results, this paper adds two new types of threat scenarios to the existing SDN vulnerability knowledge base and improves the detection efficiency by about 29%.