Modeling and Analysis of Malware Propagation for IoT Heterogeneous Devices

Abstract

With the rapid development and application of Internet of Things (IoT) technology, a large number of various types of IoT devices with security vulnerabilities have been connected to the public network. Attackers only need to use malware to successfully infect a few types of IoT devices to generate large-scale propagation in the network and capture a large number of broilers, which in turn lays the foundation for subsequent attacks. In this study, an innovative malware propagation model [i.e., IoT-susceptible-latent-propagated-recovered (IoT-SLPR)] based on epidemiological theory is developed for malware propagation in multiple IoT heterogeneous devices. The proposed model incorporates the propagation mechanism of malware in real IoT networks, and considers heterogeneous devices with different infection rates and recovery rates. This study calculates and proves the basic reproductive rate of malware and the stability of equilibrium points for different types of devices. In addition, this study designs a dynamic recovery rate optimal defense strategy, which comprehensively considers the cost and the overall infection rate of the device. The experimental results show that the proposed propagation model can effectively reflect the propagation dynamics of malware in multiple heterogeneous devices, and the achieved dynamic recovery rate defense strategy performs better than the static strategy regarding the overall results.