Abstract
The Internet of Things has been proposed for nearly 20 years. Its rich digital trace repository provides insight into people’s daily activities at home and elsewhere. On the other hand, IoT devices can become targets of attacks, or even tools for a crime. The number of civil and criminal cases involving IoT devices or services is increasing year by year. IoT forensics refers to the process of collecting, analyzing, storing and providing digital evidence in IoT devices in a legally binding manner. In particular, the traceability, integrity and tamper resistance of the evidence should be maintained. However, traditional IoT forensics architecture may be difficult to achieve these goals. This article aims to explore the combination of blockchain technology and IoT forensics which can make full use of the natural advantages of traceability and tamper resistance. A forensic architecture of the Internet of Things based on blockchain evidence is proposed, including an applications layer and data layer. The applications layer includes various APP applications, and the data layer includes the evidence analysis platform and the blockchain platform. Furthermore, an IoT forensics model including blockchain storage and supervision is proposed which can ensure the traceability and tamper-proof of forensic data.
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Acknowledgments
This work is supported by open project of National and Local Joint Engineering Laboratory of Radio Frequency Integration and Micro-assembly Technology, Nanjing University of Posts and Telecommunications (KFJJ20200201), Talent Introduction Project of Jiangsu Police Institute (JSPI19GKZL407), Scientific Research Project of Jiangsu Police Institute (2110120030) and Jiangsu Province University Student Innovation Training Program Project (202010329034Y).
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Liang, G., Xin, J., Wang, Q., Ni, X., Guo, X. (2021). A Blockchain-Based Internet of Things Forensics Model. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1424. Springer, Cham. https://doi.org/10.1007/978-3-030-78621-2_57
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DOI: https://doi.org/10.1007/978-3-030-78621-2_57
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