Malware Propagation and Prevention Model for Time-Varying Community Networks within Software Defined Networks

Lan Liu,Xiaoping Xu,Guangming Ren,Ryan K. L. Ko

doi:10.1155/2017/2910310

Abstract

As the adoption of Software Defined Networks (SDNs) grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses) in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when q<qc. The results showed that our model is effective, and the results may help to decide the SDN control strategy to defend against network malware and provide a theoretical basis to reduce and prevent network security incidents.

Highlights

With separate control and data planes for computer networking [1], Software Defined Networks (SDNs) are considered by many to be a promising network platform as it empowers programmability and flexible configuration—paving the way for more powerful network control and traffic data analysis
As the spread of network malware in SDN is similar to the spread of diseases, we can use similar models to study the spread of network malware
We discover that the time of the network malware outbreak in the subnets is dependent on the mobility rate q

Summary

Introduction

With separate control and data planes for computer networking [1], Software Defined Networks (SDNs) are considered by many to be a promising network platform as it empowers programmability and flexible configuration—paving the way for more powerful network control and traffic data analysis. With the continuous development of SDN security applications, we need to anticipate issues that might arise throughout the implementation of SDN-based security applications At their core, SDN computer networks are complex systems [2]. Compared to past computer network architectures (where it is not easy to control the whole network from the global level), SDNs are considered by many to be a promising network platform as it empowers programmability and flexible configuration—enabling powerful network control and traffic data analysis.

Background and Related Work

Modeling Network Malware Spreading in an SDN Environment

Simulation and Evaluation

Possible Applications

Conclusion and Perspectives