Modular-based secret image sharing in Internet of Things: A global progressive-enabled approach

Lina Zhang*, Xiangqin Zheng, Keping Yu, Wenjuan Li, Tao Wang, Xuan Dang, Bo Yang

*この研究の対応する著者

研究成果: Article査読

2 被引用数 (Scopus)

抄録

Due to the continuous development and progress of information technology, the Internet has also entered the era of big data based on the Internet of Things (IoT). How to protect the security of data stored and transmitted in the IoT is one of the urgent problems to be solved. This article focuses on the security issues of storage and transmission of image data in the IoT. Secret image sharing (SIS) is a kind of image protection mechanism by dividing an image into n shares, and different shares are given to different participants separately for preservation. Only when the number of shares reaches the threshold can the original image be recovered. From the perspective of image reconstruction mode, there are two types of SIS schemes: one is the traditional (k, n) threshold scheme, which provides an all-or-nothing reconstruction mode, the other is the progressive scheme, which can gradually restore the original image. In this article, a novel (k, k2) progressive secret image sharing based on modular operations is proposed, this method can divide the important images stored in the IoT into many parts and then transmit them to people in different places. It takes the whole as a unit in terms of the progressive recovery form. When the share reaches the threshold, certain blocks of the original image can be seen. As the share increases, the image will be clearer. When all shares participate in the reconstruction together, the original image can be restored without loss. Compared with other schemes, our scheme has the same smoothness, shadow size and satisfies the security, and is fine-grained progressive.

本文言語English
ジャーナルConcurrency Computation
DOI
出版ステータスAccepted/In press - 2020

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • コンピュータ サイエンスの応用
  • コンピュータ ネットワークおよび通信
  • 計算理論と計算数学

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