Lossless and Efficient Secret Image Sharing Based on Matrix Theory Modulo 256

Long, Yu; Liu, Lintao; Xia, Zhe; Yan, Xuehu; Lu, Yuliang

doi:10.3390/math8061018

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…Yu et al [19] proposed an SIS scheme modulo 256, which is not limited to the restriction that the modulo (denoted by p) of the traditional SS scheme must be a prime number, and making the shared value space correspond perfectly to the range of grayscale image pixel values. Tey frst construct an n × k sharing matrix K, which satisfes the determinant of any k × k submatrix is odd.…”

Section: Secret Sharing Based On Matrixmentioning

confidence: 99%

Generative Text Secret Sharing with Topic-Controlled Shadows

Long

Yan

et al. 2022

Security and Communication Networks

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Secret image sharing has been extensively and thoroughly researched. However, in the social network environment, shadow images are subject to compression or noise pollution during uploading and transmitting, which makes it challenging to recover secrets losslessly. Texts are more suited for transmission in social networks as shadows because of the broad variety of application scenarios and inherent robustness. Through a secret sharing technique of k , n threshold, a secret is encrypted as n shadows, where any k or more shadows can recover the secret, while less than k cannot obtain any information on the secret. In this article, we propose a generative text secret sharing scheme with topic-controlled shadows, which encrypts a secret message as a number of semantically natural shadow texts and controls the topics of shadow texts using bag-of-words models during text generation by the language model. This study also proposes two goal programming models to improve the shadow texts’ topic relevance and fluency. The shadow texts of the proposed scheme satisfy loss tolerance, semantic comprehensibility, topic controllability, and robustness. An ablation study, comparative test, and anti-detection experiment verify the effectiveness of the proposed scheme.

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Section: Secret Sharing Based On Matrixmentioning

confidence: 99%

Generative Text Secret Sharing with Topic-Controlled Shadows

Long

Yan

et al. 2022

Security and Communication Networks

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“…In recent years, researchers have proposed more SIS schemes, including schemes for color images [12,13], progressive decoding [14,15], meaningful shares [16], and minimizing pixel expansion [17,18], etc. In addition, there exist novel SIS schemes based on various theorems, like matrix theory [19], non-full rank linear model [20] and natural steganography (NS) [21]. More methods of steganography and multimedia security [22,23] are given in these years.…”

Section: Introductionmentioning

confidence: 99%

Two-in-One Secret Image Sharing Scheme with Higher Visual Quality of the Previewed Image

2022

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Secret image sharing (SIS) scheme is a secret image encoding and decoding scheme that reconstructs the secret image only if the number of participants is sufficient. In contrast, inadequate participants gain no information about the secret image. Two-in-one secret image sharing (TiOSIS) scheme is a kind of SIS scheme with two decoding options, quick preview without computation and accurate recovery with computer. For higher decoding speed, Li et al. proposed an improved two-in-one secret image sharing scheme, utilizing Boolean operation for less computational complexity, where the visual quality of the previewed image is deteriorated. In this paper, we use q-bit gray visual cryptography to build a mathematical model for better visual quality of the previewed image based on Li et al.’s TiOSIS scheme. The black sub-pixels of shadows corresponding to a black secret pixel are replaced by a q-bit grayscale value rather than an 8-bit grayscale value where q is a positive integer smaller than 8. The theoretical analysis and experiments are exhibited to guarantee feasibility and effectiveness of the proposed scheme.

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“…To put it briefly, the current methods for restoring images without loss have issues like spreading of pixels, an uneven distribution of pixels in shadow images, and a significant amount of computational expenses. The issue of lossless recovery has been addressed by Long Yu and his team [30] through the utilization of matrix computations in modulo 256. However, their approach necessitates a matrix multiplication for every shadow image pixel value, resulting in a significant amount of computations required for shadow image calculation.…”

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confidence: 99%

LWE‐based verifiable essential secret image sharing scheme ((t,s,k,n)$( {t,s,k,n} )$ ‐ VESIS)

Dehkordi,

Farahi,

Mashhadi

2023

IET Image Processing

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In traditional secret image sharing schemes, shareholders have similar situations, and to recover the secret image, they must be present as many as the threshold. However, in scenarios where the shareholders occupy different positions, essential and non‐essential, the use of essential secret image sharing schemes becomes necessary. This article presents a novel verifiable essential secret image sharing scheme based on LWEs that incorporates Bloom filters and hash functions for verification purposes. The proposed scheme for a secret image does not require any pre‐processing. The shadow images of both essential and non‐essential shareholders are of the same size, eliminating the need for concatenating sub‐shadows. Furthermore, shadow images for essential and non‐essential shareholders are produced simultaneously in a single step. The scheme is also quantum safe thanks to the use of quantum‐resistant primitives. The experimental results confirm the security and efficiency of the proposed scheme.

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Lossless and Efficient Secret Image Sharing Based on Matrix Theory Modulo 256

Cited by 5 publications

References 27 publications

Generative Text Secret Sharing with Topic-Controlled Shadows

Generative Text Secret Sharing with Topic-Controlled Shadows

Two-in-One Secret Image Sharing Scheme with Higher Visual Quality of the Previewed Image

LWE‐based verifiable essential secret image sharing scheme ((t,s,k,n)$( {t,s,k,n} )$ ‐ VESIS)

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