Sharing secret messages using meaningful digital shadow images

In the traditional secret image sharing, the secret image is encoded into two or more meaningless image shares, and single share cannot derive any information about the secret image. The meaningless image shares are insecure which may attract the notice of attackers during transmission process. More...

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書目詳細資料
主要作者: Võ Phước Hưng
其他作者: Prof. Chin-Chen Chang (Người hướng dẫn Khoa học)
語言:eng
出版: Trường ĐH Phùng Giáp 2023
在線閱讀:https://opac.tvu.edu.vn/pages/opac/wpid-detailbib-id-43007.html
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Thư viện lưu trữ: Trung tâm Học liệu – Phát triển Dạy và Học, Trường Đại học Trà Vinh
實物特徵
總結:In the traditional secret image sharing, the secret image is encoded into two or more meaningless image shares, and single share cannot derive any information about the secret image. The meaningless image shares are insecure which may attract the notice of attackers during transmission process. Moreover, the meaningless share images are difficult to identify and manage in a large image database. Therefore, in 2007, Yang et al. proposed a user-friendly (k, n)-threshold scheme based on Shamir’s polynomial with different primes. Their method calculated differences between pixels in a block and their left pixels. According to the differences, the prime number for the Shamir’s polynomial can be decided and the differences were distributed to shares by using Shamir’s polynomial. This study proposes two novel user-friendly image sharing schemes. The first scheme uses polynomials with different primes to generate pixel shadows without adjusting the LSBs of original pixels, so that the recovery process can reconstruct a highquality original image using the Lagrange interpolation function. The second scheme develops an image-sharing system by using JPEG-LS prediction technique to classify prime numbers for encoding blocks. Owing to the involvement of JPEG-LS prediction technique, the produced differences not only refer to the left pixel but also their neighboring pixels. Therefore, the values of differences become small. This leads to high quality of the reconstructed image. Experimental results also confirm our statements.