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Article type: Research Article
Authors: Liu, Donglan; * | Zhang, Hao | Wang, Rui | Zhang, Fangzhe | Sun, Lili | Liu, Xin | Ma, Lei
Affiliations: State Grid Shandong Electric Power Research Institute, Jinan 250003, Shandong, China
Correspondence: [*] Corresponding author. E-mail: [email protected].
Abstract: In recent years, with the rapid development of IoT technology, hundreds of millions of IoT devices have been manufactured and applied, and the subsequent IoT attacks have become more and more severe. The complex and diverse architecture of IoT devices, coupled with the lack of security development specifications by IoT device manufacturers, and the widespread misuse and abuse of code, lead to the proliferation of IoT vulnerabilities. The conventional IoT vulnerability detection scheme is expensive to operate, and the implementation technology is complex, which is difficult to be fully promoted. This paper proposes a lightweight IoT firmware vulnerability detection scheme based on homology detection. The processing is converted into a feature vector, which effectively reduces the platform dependence. Combined with the database technology, the storage and retrieval efficiency is increased, and the same-origin vulnerability detection is realized by calculating the cosine similarity of the vector. The experimental results show that this scheme can effectively identify the vulnerabilities in firmware.
Keywords: Internet of Things, firmware, vulnerability detection, homology detection
DOI: 10.3233/JHS-222027
Journal: Journal of High Speed Networks, vol. 28, no. 4, pp. 287-297, 2022
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