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Secret Data-Driven Carrier-Free Secret Sharing Scheme Based on Error Correction Blocks of QR Codes

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Data Science (ICPCSEE 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 727))

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Abstract

In this paper, a novel secret data-driven carrier-free (semi structural formula) visual secret sharing (VSS) scheme with (2, 2) threshold based on the error correction blocks of QR codes is investigated. The proposed scheme is to search two QR codes that altered to satisfy the secret sharing modules in the error correction mechanism from the large datasets of QR codes according to the secret image, which is to embed the secret image into QR codes based on carrier-free secret sharing. The size of secret image is the same or closest with the region from the coordinate of (7, 7) to the lower right corner of QR codes. In this way, we can find the QR codes combination of embedding secret information maximization with secret data-driven based on Big data search. Each output share is a valid QR code which can be decoded correctly utilizing a QR code reader and it may reduce the likelihood of attracting the attention of potential attackers. The proposed scheme can reveal secret image visually with the abilities of stacking and XOR decryptions. The secret image can be recovered by human visual system (HVS) without any computation based on stacking. On the other hand, if the light-weight computation device is available, the secret image can be lossless revealed based on XOR operation. In addition, QR codes could assist alignment for VSS recovery. The experimental results show the effectiveness of our scheme.

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Correspondence to Song Wan or Xuehu Yan .

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Wan, S., Lu, Y., Yan, X., Liu, H., Tan, L. (2017). Secret Data-Driven Carrier-Free Secret Sharing Scheme Based on Error Correction Blocks of QR Codes. In: Zou, B., Li, M., Wang, H., Song, X., Xie, W., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-6385-5_20

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  • DOI: https://doi.org/10.1007/978-981-10-6385-5_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6384-8

  • Online ISBN: 978-981-10-6385-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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