Ming Zhang, Zhe Sun, Hui Li, Ben Niu, Fenghua Li, Zixu Zhang, Yuhang Xie, Chunhao Zheng
{"title":"Go-Sharing: A Blockchain-Based Privacy-Preserving Framework for Cross-Social Network Photo Sharing","authors":"Ming Zhang, Zhe Sun, Hui Li, Ben Niu, Fenghua Li, Zixu Zhang, Yuhang Xie, Chunhao Zheng","doi":"10.1109/TDSC.2022.3208934","DOIUrl":null,"url":null,"abstract":"The evolution of social media has led to a trend of posting daily photos on online Social Network Platforms (SNPs). The privacy of online photos is often protected carefully by security mechanisms. However, these mechanisms will lose effectiveness when someone spreads the photos to other platforms. In this article, we propose Go-sharing, a blockchain-based privacy-preserving framework that provides powerful dissemination control for cross-SNP photo sharing. In contrast to security mechanisms running separately in centralized servers that do not trust each other, our framework achieves consistent consensus on photo dissemination control through carefully designed smart contract-based protocols. We use these protocols to create platform-free dissemination trees for every image, providing users with complete sharing control and privacy protection. Considering the possible privacy conflicts between owners and subsequent re-posters in cross-SNP sharing, we design a dynamic privacy policy generation algorithm that maximizes the flexibility of re-posters without violating formers’ privacy. Moreover, Go-sharing also provides robust photo ownership identification mechanisms to avoid illegal reprinting. It introduces a random noise black box in a two-stage separable deep learning process to improve robustness against unpredictable manipulations. Through extensive real-world simulations, the results demonstrate the capability and effectiveness of the framework across a number of performance metrics.","PeriodicalId":13047,"journal":{"name":"IEEE Transactions on Dependable and Secure Computing","volume":"20 1","pages":"3572-3587"},"PeriodicalIF":7.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Dependable and Secure Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/TDSC.2022.3208934","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 2
Abstract
The evolution of social media has led to a trend of posting daily photos on online Social Network Platforms (SNPs). The privacy of online photos is often protected carefully by security mechanisms. However, these mechanisms will lose effectiveness when someone spreads the photos to other platforms. In this article, we propose Go-sharing, a blockchain-based privacy-preserving framework that provides powerful dissemination control for cross-SNP photo sharing. In contrast to security mechanisms running separately in centralized servers that do not trust each other, our framework achieves consistent consensus on photo dissemination control through carefully designed smart contract-based protocols. We use these protocols to create platform-free dissemination trees for every image, providing users with complete sharing control and privacy protection. Considering the possible privacy conflicts between owners and subsequent re-posters in cross-SNP sharing, we design a dynamic privacy policy generation algorithm that maximizes the flexibility of re-posters without violating formers’ privacy. Moreover, Go-sharing also provides robust photo ownership identification mechanisms to avoid illegal reprinting. It introduces a random noise black box in a two-stage separable deep learning process to improve robustness against unpredictable manipulations. Through extensive real-world simulations, the results demonstrate the capability and effectiveness of the framework across a number of performance metrics.
期刊介绍:
The "IEEE Transactions on Dependable and Secure Computing (TDSC)" is a prestigious journal that publishes high-quality, peer-reviewed research in the field of computer science, specifically targeting the development of dependable and secure computing systems and networks. This journal is dedicated to exploring the fundamental principles, methodologies, and mechanisms that enable the design, modeling, and evaluation of systems that meet the required levels of reliability, security, and performance.
The scope of TDSC includes research on measurement, modeling, and simulation techniques that contribute to the understanding and improvement of system performance under various constraints. It also covers the foundations necessary for the joint evaluation, verification, and design of systems that balance performance, security, and dependability.
By publishing archival research results, TDSC aims to provide a valuable resource for researchers, engineers, and practitioners working in the areas of cybersecurity, fault tolerance, and system reliability. The journal's focus on cutting-edge research ensures that it remains at the forefront of advancements in the field, promoting the development of technologies that are critical for the functioning of modern, complex systems.