Comprehensive Vulnerability Detection and Malware Infection Testing Strategies for IoT Devices

Bo-Hao Liang, Ren-Hung Hwang, Jia-You Lin, Hsiao-Hwa Chen

Abstract: With the increasing prevalence of Internet of Things (IoT) devices, security vulnerabilities and malware infections have emerged as significant risks. To address these challenges, advanced vulnerability detection tools are essential for enhancing IoT security assessments. In this study, we analyzed common vulnerabilities and evolving attack methodologies to develop improved detection techniques. Our research focuses on two key areas: 1) comprehensive vulnerability detection and 2) malware infection testing strategies. Through on-site testing and detailed analysis, we identified prevalent security flaws in IoT devices and developed a suite of tools tailored for detecting these vulnerabilities. Additionally, we discovered that some devices exhibit inherent immunity to specific malware strains, emphasizing the need for novel malware infection detection strategies. Real-world evaluations uncovered previously unknown vulnerabilities and weaknesses, revealed widespread susceptibility to DoS attacks, and demonstrated that not all devices are vulnerable to malware infections. These findings confirm the effectiveness of our approach in identifying risks and enhancing IoT security.

External IDs:dblp:journals/iotj/LiangHLC25