Abstract
The early research on IoT (Internet of Things) firmware is mostly based on the hardware environment, the software interfaces and hardware resources are very limited, and the traditional dynamic debugging and fuzzing tools cannot be executed efficiently, which leads to high research costs. In order to solve this problem, a simulation-based fuzzing prototype tool for smart IoT devices (IoTSFT) is proposed in this paper. It builds a pure software virtual environment to make the firmware run out of hardware constraints. In addition, the security analysis of the firmware can be completed by combining the path coverage-based fuzzing technology. It is verified by experiments that IoTSFT can successfully simulate binary, obtain the sample execution path coverage, and fuzz the target binary.
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References
Bellard F.: QEMU, a fast and portable dynamic translator. In: USENIX Annual Technical Conference, FREENIX Track, vol. 41, p. 46 (2005)
Chen, D.D., Woo, M., Brumley, D., Egele, M.: Towards automated dynamic analysis for linux-based embedded firmware. In: NDSS, vol. 1, p. 1 (2016)
Fang, J., Bao, Q., Song, S.: Network device firmware running analysis based on QEMU. In: 2015 International Conference on Information Computer and Communication Engineering (ICC2015), pp. 1–10 (2015)
Zheng, Y., Davanian, A., Yin, H., Song, C., Zhu, H., Sun, L.: FIRM-AFL: high-throughput greybox fuzzing of IoT firmware via augmented process emulation. In: 28th {USENIX} Security Symposium ({USENIX} Security 19), pp. 1099–1114 (2019)
Li, J., Zhao, B., Zhang, C.: Fuzzing: a survey. Cybersecurity 1, 1–13 (2018)
Chen, C., Cui, B., Ma, J., Wu, R., Guo, J., Liu, W.: A systematic review of fuzzing techniques. Comput. Secur. 75, 118–137 (2018)
American Fuzzy Lop. https://lcamtuf.coredump.cx/afl/. Accessed on 31 March 2021
Amini, P.: Fuzzing frameworks. In: Black Hat USA, vol. 14, pp. 211–217 (2007)
Nethercote, N.: Dynamic Binary Analysis and Instrumentation, pp. 1–8. University of Cambridge, Computer Laboratory, (No. UCAM-CL-TR-606) (2004)
Yang, W., Wang, Y., Cui, B., Chen, C.: A Static Instrumentation Method for ELF Binary. In: Barolli, L., Xhafa, F., Hussain, O. (eds.) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2019. Advances in Intelligent Systems and Computing, vol. 994. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-22263-5_38
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This article is supported by the National Natural Science Foundation of China (No. 61872386).
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Zhang, F., Cui, B., Chen, C., Sun, Y., Gong, K., Ma, J. (2022). Simulation-Based Fuzzing for Smart IoT Devices. In: Barolli, L., Yim, K., Chen, HC. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2021. Lecture Notes in Networks and Systems, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-030-79728-7_30
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DOI: https://doi.org/10.1007/978-3-030-79728-7_30
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