Comprehensive Vulnerability Detection and Malware Infection Testing Strategies for IoT Devices

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.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-02-20
DOI
https://doi.org/10.1109/jiot.2025.3543819
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.49
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article

Comprehensive Vulnerability Detection and Malware Infection Testing Strategies for IoT Devices

Ren‐Hung Hwang, Baojun Liang, Jia-You Lin, Hsiao‐Hwa Chen
1 citations
IEEE Internet of Things Journal
Advanced Malware Detection Techniques
1.49
article

Comprehensive Vulnerability Detection and Malware Infection Testing Strategies for IoT Devices

Ren‐Hung Hwang, Baojun Liang, Jia-You Lin, Hsiao‐Hwa Chen
article en
1 citations

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.

IEEE Internet of Things JournalVol. 12(12)
National Chung Cheng University (TW), National Yang Ming Chiao Tung University (TW), National Cheng Kung University (TW)
Openalex Percentile: Top 23%
Advanced Malware Detection Techniques
1.49
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Comprehensive Vulnerability Detection and Malware Infection Testing Strategies for IoT Devices — Ren‐Hung Hwang, Baojun Liang, et al. · IEEE Internet of Things Journal (2025) | TGRS Research Map | TGRS