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Achieving intelligent Trust-Layer for Internet-of-Things via Self-Redactable blockchain

Huang, K., Zhang, X., Mu, Y., Rezaeibagha, F., Du, X. and Guizani, N. (2020) Achieving intelligent Trust-Layer for Internet-of-Things via Self-Redactable blockchain. IEEE Transactions on Industrial Informatics, 16 (4). pp. 2677-2686.

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The advances of artificial intelligence (AI) propels big data processing and transmission for Internet of Things (IoT), by capturing and structuring big data produced by heterogeneous devices. While applying blockchain to manage IoT devices and associated big data, the blockchain itself suffers from abuse of decentralization from anonymous users. Specifically, it has been utilized to facilitate black market trades and illegal activities. Ateniese et al. proposed using the chameleon hash (CH) to derive redactable blockchain (EuroS&P), which works by embedding a trapdoor in the basic hash function so that block content can be rewritten without causing major hard forks. In short, the redacted block hash remains unchanged. However, there is lacking intelligent design where any mistakes observed in the chain can be corrected universally and automatically. This creates disincentives to use redactable blockchain (RB) for managing big data or any data-driven business mainly due to ineffective chain redaction. To solve this problem, in this article, we propose the notion of the self-redactable blockchain (SRB) to support intelligent execution of chain redaction. Specifically, we propose the first revocable chameleon hash (RCH) to power RB. It enables an ephemeral trapdoor for finding collision without any co-operation. Periodical expiration is applied to committed hash and an ephemeral trapdoor to prevent any abuses of redaction power. We instantiate how to use our RCH to build SRB as an intelligent trust-layer for IoT. We also give a rigorous analysis as well as comprehensive experiments to validate our proposals. The evidence showed that our proposal is secure and acceptably efficient for IoT devices.

Item Type: Journal Article
Murdoch Affiliation(s): Engineering and Energy
Publisher: IEEE
Copyright: © 2020 IEEE
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