Empirical Study of System Resources Abused by IoT Attackers

IoT devices have been under frequent attacks in recent years, causing severe impacts. Previous research has shown the evolution and features of some specific IoT malware families or stages of IoT attacks through offline sample analysis. However, we still lack a systematic observation of various system resources abused by active attackers and the malicious intentions behind these behaviors. This makes it difficult to design appropriate protection strategies to defend against existing attacks and possible future variants. In this paper, we fill this gap by analyzing 117,862 valid attack sessions captured by our dedicated high-interaction IoT honeypot, HoneyAsclepius, and further discover the intentions in our designed workflow. HoneyAsclepius enables high capture capability as well as continuous behavior monitoring during active attack sessions in real-time. Through a large-scale deployment, we collected 11,301,239 malicious behaviors originating from 50,594 different attackers. Based on this information, we further separate the behaviors in different attack sessions targeting distinct categories of system resources, estimate the temporal relations and summarize their malicious intentions behind. Inspired by such investigations, we present several key insights about abusive behaviors of the file, network, process, and special capability resources, and further propose practical defense strategies to better protect IoT devices.