Blockchain-Based Image Sharing Application

2020 ◽  
pp. 46-59
Author(s):  
Zhen-Kai Wong ◽  
Swee-Huay Heng
Keyword(s):  
Image Sharing

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 Assisting humans in privacy management: an agent-based approach

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
A. Can Kurtan ◽  
Pınar Yolum
Keyword(s):  
Online Social Networks ◽  
Online Social Network ◽  
Real Life ◽  
Privacy Management ◽  
Agent Based ◽  
Image Sharing ◽  
Privacy Preferences ◽  
Privacy Settings ◽  
Privacy Setting ◽  
Sharing Behavior

AbstractImage sharing is a service offered by many online social networks. In order to preserve privacy of images, users need to think through and specify a privacy setting for each image that they upload. This is difficult for two main reasons: first, research shows that many times users do not know their own privacy preferences, but only become aware of them over time. Second, even when users know their privacy preferences, editing these privacy settings is cumbersome and requires too much effort, interfering with the quick sharing behavior expected on an online social network. Accordingly, this paper proposes a privacy recommendation model for images using tags and an agent that implements this, namely pelte. Each user agent makes use of the privacy settings that its user have set for previous images to predict automatically the privacy setting for an image that is uploaded to be shared. When in doubt, the agent analyzes the sharing behavior of other users in the user’s network to be able to recommend to its user about what should be considered as private. Contrary to existing approaches that assume all the images are available to a centralized model, pelte is compatible to distributed environments since each agent accesses only the privacy settings of the images that the agent owner has shared or those that have been shared with the user. Our simulations on a real-life dataset shows that pelte can accurately predict privacy settings even when a user has shared a few images with others, the images have only a few tags or the user’s friends have varying privacy preferences.

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.

scholarly journals Multisite Image Data Collection and Management Using the RSNA Image Sharing Network

2014 ◽  
Vol 7 (1) ◽  
pp. 36-39 ◽  
Author(s):  
Bradley J. Erickson ◽  
Patricio Fajnwaks ◽  
Steve G. Langer ◽  
John Perry
Keyword(s):  
Data Collection ◽  
Image Data ◽  
Image Sharing ◽  
Collection And Management

K out of N Secret Sharing Scheme for Multiple Color Images with Steganography and Authentication

2016 ◽  
Vol 16 (02) ◽  
pp. 1650010 ◽  
Author(s):  
P. Mohamed Fathimal ◽  
P. Arockia Jansi Rani
Keyword(s):  
Secret Sharing ◽  
Visual Quality ◽  
Color Images ◽  
Pixel Expansion ◽  
Image Sharing ◽  
Digital Ecosystem ◽  
Sharing Scheme ◽  
Text Steganography ◽  
Key Aspects

With our lives trundling toward a fully-digital ecosystem in break-neck speed, today’s encryption and cryptography are facing the challenge of ensuring security and future-readiness of our transactions. When such transactions involve multiple hands, transmission of such data in discrete and recoverable parts (secret shares) guarantees confidentiality. This paper’s objective is to present a foolproof way of multiple secret sharing, eliminating issues such as half-toning and degradation of visual quality of the recovered images. This [Formula: see text] out of [Formula: see text] steganography and authenticated image sharing (SAIS) scheme for multiple color images generates [Formula: see text] relevant shares with the ability to reconstruct the secret images using [Formula: see text] shares and facility to find out any move for appropriation of share cover images. The key aspects of this proposed scheme is to use simple Boolean and arithmetic operations with reduction of computational complexity from [Formula: see text] to [Formula: see text] and to share multiple images without any pixel expansion.

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

scholarly journals Teen Girls’ Experiences Negotiating the Ubiquitous Dick Pic: Sexual Double Standards and the Normalization of Image Based Sexual Harassment

Sex Roles ◽  
2021 ◽  
Author(s):  
Jessica Ringrose ◽  
Kaitlyn Regehr ◽  
Sophie Whitehead
Keyword(s):  
Social Media ◽  
Sexual Harassment ◽  
Focus Group Interviews ◽  
Double Standards ◽  
Media Image ◽  
Image Sharing ◽  
Social Currency ◽  
Social Media Platforms ◽  
Group Interviews ◽  
Sexual Double Standards

AbstractA range of important studies have recently explored adult women’s experiences of receiving unwanted dick pics (Amundsen, 2020). However, to date there has been limited research that has explored teen girls’ experiences of receiving unwanted penis images in depth. To address this gap we draw upon our findings from a qualitative study using focus group interviews and arts based drawing methods to explore social media image sharing practices with 144 young people aged 11–18 in seven secondary schools in England. We argue that being bombarded with unwanted dick pics on social media platforms like Snapchat normalises harassing practices as signs of desirability and popularity for girls, but suggest that being sent unsolicited dick pics from boys at school is more difficult for girls to manage or report than ignoring or blocking random older senders. We also found that due to sexual double standards girls were not able to leverage dick pics for status in the same way boys can use girls’ nudes as social currency, since girls faced the possibility of being shamed for being known recipients of dick pics. Finally we explore how some girls challenge abusive elements of toxic masculinity in the drawing sessions and our conclusion argues that unwanted dick pics should always be understood as forms of image based sexual harassment.

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