Suppression of Malicious Code Propagation in Software-Defined Networking

Abstract

The flexibility and programmability of SDN enable dynamic and automated network configuration and traffic routing. However, this also provides more avenues for malicious code propagation, leading to serious risks such as service disruptions and privacy breaches. To address this problem, we first designed three modules to suppress malicious code propagation: the abnormal traffic detection module, the malicious code analysis module, and the abnormal traffic tracing module. Then, the sharing mechanism is introduced. In order to analyze the process of malicious code propagation more clearly, based on the above strategy, this paper introduces the warning node into the classical SIR model, which can be exploited for studying how to control malicious code propagation to prevent large-scale outbreaks. The propagation threshold and equilibrium point of the proposed model are obtained through calculations. By constructing a Lyapunov function, the equilibrium point is proven stable. Finally, numerical simulation results indicate that when the detection rate reaches 90%, approximately 86.3% fewer nodes are infected at the peak point. Through comparative analysis, our system demonstrates optimal performance, validating the effectiveness of the analytical results.