A Progressive Threshold Secret Image Sharing with Meaningful Shares for Gray-Scale Image

2016 ◽  
Author(s):  
Lintao Liu ◽  
Yuliang Lu ◽  
Xuehu Yan ◽  
Song Wan
Keyword(s):  
Secret Image Sharing ◽  
Gray Scale ◽  
Secret Image ◽  
Meaningful Shares ◽  
Image Sharing ◽  
Gray Scale Image

scholarly journals A novel method for secret image sharing Using nibble exchange

2013 ◽  
Vol 4 (1) ◽  
pp. 94-97
Author(s):  
Anirban Chakraborty ◽  
Subhendu Das
Keyword(s):  
Linear Time ◽  
Secret Image Sharing ◽  
Gray Scale ◽  
Secret Image ◽  
Image Sharing ◽  
Novel Method

This paper proposes a new scheme for secret image sharing which shuffles and manipulates the nibbles (and hence the bytes) of the pixel values of the images. We have developed a new algorithm called LDRU (Left-Down-Right-Up) for the construction of shares. Using LDRU algorithm any type of (Binary, Gray scale or Color) secret images can be shared and reconstructed precisely in linear time.

scholarly journals Improvements in Geometry-Based Secret Image Sharing Approach with Steganography

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Mustafa Ulutas ◽  
Vasif V. Nabiyev ◽  
Guzin Ulutas
Keyword(s):  
Secret Sharing ◽  
The Internet ◽  
Secret Sharing Scheme ◽  
Secret Image Sharing ◽  
Sensitive Data ◽  
Secret Image ◽  
Meaningful Shares ◽  
Image Sharing ◽  
Sharing Scheme ◽  
Fast Development

Protection of the sensitive data is an important issue because of the fast development of applications that need exchange of the secret information over the Internet. Secret sharing is an idea proposed by Shamir and Blakley separately with different implementations in 1979. Lin and Tsai proposed a method that uses Steganography to create meaningful shares by using Shamir's secret sharing scheme in 2004. In recent years, researchers work to remove some of the weaknesses of this method. However, all of these methods need cover images four times bigger than the secret image. This arises two problems: increased storage and bandwidth need for shares. We used cover images with the same size as the secret image by using both Blakley's secret sharing approach and Steganography. Therefore, we achieved reduced storage and transmission bandwidth for shares. Besides, the proposed method creates meaningful shares by using Steganography instead of noise-like shares, different from other studies that use Blakley's approach.

Secret image sharing and its algebraic coding method

2013 ◽  
Vol 32 (3) ◽  
pp. 669-678
Author(s):  
Xiao-jing WANG ◽  
Jia-jia FANG ◽  
Hong-liang CAI ◽  
Yi-ding WANG
Keyword(s):  
Secret Image Sharing ◽  
Secret Image ◽  
Image Sharing ◽  
Coding Method

scholarly journals Robust Secret Image Sharing Resistant to Noise in Shares

2021 ◽  
Vol 17 (1) ◽  
pp. 1-22
Author(s):  
Xuehu Yan ◽  
Lintao Liu ◽  
Longlong Li ◽  
Yuliang Lu
Keyword(s):  
Chinese Remainder Theorem ◽  
Recovery Phase ◽  
Error Correcting Codes ◽  
Secret Image Sharing ◽  
Data Loss ◽  
Least Significant Bit ◽  
Recovery Method ◽  
Secret Image ◽  
Image Sharing ◽  
Salt And Pepper

A secret image is split into   shares in the generation phase of secret image sharing (SIS) for a  threshold. In the recovery phase, the secret image is recovered when any   or more shares are collected, and each collected share is generally assumed to be lossless in conventional SIS during storage and transmission. However, noise will arise during real-world storage and transmission; thus, shares will experience data loss, which will also lead to data loss in the secret image being recovered. Secret image recovery in the case of lossy shares is an important issue that must be addressed in practice, which is the overall subject of this article. An SIS scheme that can recover the secret image from lossy shares is proposed in this article. First, robust SIS and its definition are introduced. Next, a robust SIS scheme for a  threshold without pixel expansion is proposed based on the Chinese remainder theorem (CRT) and error-correcting codes (ECC). By screening the random numbers, the share generation phase of the proposed robust SIS is designed to implement the error correction capability without increasing the share size. Particularly in the case of collecting noisy shares, our recovery method is to some degree robust to some noise types, such as least significant bit (LSB) noise, JPEG compression, and salt-and-pepper noise. A theoretical proof is presented, and experimental results are examined to evaluate the effectiveness of our proposed method.

Distortion less secret image sharing scheme for Internet of Things system

2017 ◽  
Vol 22 (S1) ◽  
pp. 2293-2307 ◽  
Author(s):  
Li Li ◽  
M. Shamim Hossain ◽  
Ahmed A. Abd El-Latif ◽  
M. F. Alhamid
Keyword(s):  
Internet Of Things ◽  
Secret Image Sharing ◽  
Secret Image ◽  
Image Sharing ◽  
Sharing Scheme ◽  
Secret Image Sharing Scheme
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