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Toward Personal Data Sharing Autonomy: A Task-Driven Data Capsule Sharing System

delete2024-01-01
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PRE
AI
Q
Qiuyun Lyu
Y
Yilong Zhou
Y
Yizhi Ren *
Z
Zhen Wang
Y
Yunchuan Guo
DOI:10.1109/TIFS.2024.3472529delete
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摘要

摘要

En 中文
Personal data custodian services enable data owners to share their data with data consumers in a convenient manner, anytime and anywhere. However, with data hosted in these services being beyond the control of the data owners, it raises significant concerns about privacy in personal data sharing. Many schemes have been proposed to realize fine-grained access control and privacy protection in data sharing. However, they fail to protect the rights of data owners to their data under the law, since their designs focus on the management of system administrators rather than enhancing the data owners' privacy. In this paper, we introduce a novel task-driven personal data sharing system based on the data capsule paradigm realizing personal data sharing autonomy. It enables data owners in our system to fully control their data, and share it autonomously. Specifically, we present a tamper-resistant data capsule encapsulation method, where the data capsule is the minimal unit for independent and secure personal data storage and sharing. Additionally, to realize selective sharing and informed-consent based authorization, we propose a task-driven data sharing mechanism that is resistant to collusion and EDoS attacks. Furthermore, by updating parts of the data capsules, the permissions granted to data consumers can be immediately revoked. Finally, we conduct a security and performance analysis, proving that our scheme is correct, sound, and secure, as well as revealing more advantageous features in practicality, compared with the state-of-the-art schemes.
Keyword:
Data privacy
Authorization
Encryption
Encapsulation
Protection
Software
Regulation
Memory
Information sharing
Resistance
Personal data sharing autonomy
data capsule
task-driven

期刊

IEEE Transactions on Information Forensics and Security 封面图
IEEE Transactions on Information Forensics and Security
IF:
8
论文数:
5.2K
被引数:
2.3W

机构

H
Hangzhou Dianzi University
学者数:
1.3W
论文数: 9.6K
被引数: 7.5K
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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