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Broadcasting Steganography in the Blockchain

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Digital Forensics and Watermarking (IWDW 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12022))

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Abstract

Conventional steganography embeds secret data into an innocent cover object such as image and video. The resulting stego object will be sent to the desired receiver via an insecure channel. Though the channel monitor cannot distinguish between normal objects and objects containing hidden information, he has the ability to intercept and alter the objects so as to break down the covert communication. It inspires us to introduce new steganography in Blockchain in order to overcome the aforementioned problem since an attacker cannot tamper Blockchain data once a block was generated, meaning that, a receiver will always be able to fully retrieve the secret data with the secret key. For the proposed work, the miner serves as the steganographer, who embeds secret data into the transactions within a block during the process of generating the block. To secure the data embedding process within a block, we choose a part of transactions in a block according to a secret key, and embed the secret data by repeatable-address arrangement. Our analysis demonstrates that, it is difficult for an attacker to extract the embedded data. Since the miner collects normal transactions for generating a block and does not generate abnormal transactions, the data embedding process will not arouse suspicion, providing a high level of security.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Bitcoin_network.

  2. 2.

    https://www.blockchain.com/explorer?currency=BTC&stat=transactions.

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Acknowledgement

This work was partly supported by the National Natural Science Foundation of China (NSFC) (U1636206, 61525203, and 61902235), the Shanghai Institute for Advanced Communication and Data Science, and the Natural Science Foundation of Shanghai (19ZR1419000).

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Correspondence to Hanzhou Wu .

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Xu, M., Wu, H., Feng, G., Zhang, X., Ding, F. (2020). Broadcasting Steganography in the Blockchain. In: Wang, H., Zhao, X., Shi, Y., Kim, H., Piva, A. (eds) Digital Forensics and Watermarking. IWDW 2019. Lecture Notes in Computer Science(), vol 12022. Springer, Cham. https://doi.org/10.1007/978-3-030-43575-2_22

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  • DOI: https://doi.org/10.1007/978-3-030-43575-2_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43574-5

  • Online ISBN: 978-3-030-43575-2

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