Abstract
Cyberattacks targeting vulnerabilities in the internet of things (IoT) devices are increasing in number annually. Accordingly, various methods and analysis tools for IoT vulnerability detection have been proposed. Each analysis tool focuses on a specific vulnerability; therefore, it is necessary to use different analysis tools to detect multiple vulnerabilities. However, the currently available analysis tools often suffer from installation errors and are difficult to use effectively. Therefore, we propose a middleware for static analysis of IoT firmware that can be equipped with multiple vulnerability-detection algorithms. Using our middleware, multiple vulnerability-detection algorithms can be combined into a single analysis tool. Our results were compared with those of Karonte, the most popular analysis tool in terms of capability.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers JP21H03496, JP22K12157, JP23H03688 and SEI Group CSR Foundation.
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Yoda, M., Nakamura, S., Sei, Y., Tahara, Y., Ohsuga, A. (2024). A Scalable Middleware for IoT Vulnerability Detection. In: Lee, R. (eds) Networking and Parallel/Distributed Computing Systems. Studies in Computational Intelligence, vol 1125. Springer, Cham. https://doi.org/10.1007/978-3-031-53274-0_7
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