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基于 GDPR 下的个人数据使用的智能合约式动态同意管理系统。

A Smart Contract-Based Dynamic Consent Management System for Personal Data Usage under GDPR.

机构信息

Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea.

Department of Computer Engineering, Hongik University, Seoul 04066, Korea.

出版信息

Sensors (Basel). 2021 Nov 30;21(23):7994. doi: 10.3390/s21237994.

Abstract

A massive amount of sensitive personal data is being collected and used by scientists, businesses, and governments. This has led to unprecedented threats to privacy rights and the security of personal data. There are few solutions that empower individuals to provide systematic consent agreements on distinct personal information and control who can collect, access, and use their data for specific purposes and periods. Individuals should be able to delegate consent rights, access consent-related information, and withdraw their given consent at any time. We propose a smart-contract-based dynamic consent management system, backed by blockchain technology, targeting personal data usage under the general data protection regulation. Our user-centric dynamic consent management system allows users to control their personal data collection and consent to its usage throughout the data lifecycle. Transaction history and logs are recorded in a blockchain that provides trusted tamper-proof data provenance, accountability, and traceability. A prototype of our system was designed and implemented to demonstrate its feasibility. The acceptability and reliability of the system were assessed by experimental testing and validation processes. We also analyzed the security and privacy of the system and evaluated its performance.

摘要

大量敏感的个人数据正被科学家、企业和政府收集和使用。这导致了对隐私权利和个人数据安全的前所未有的威胁。几乎没有任何解决方案可以使个人能够就不同的个人信息提供系统的同意协议,并控制谁可以在特定目的和期限内收集、访问和使用他们的数据。个人应该能够随时委托同意权、访问与同意相关的信息,并撤回他们的同意。我们提出了一种基于智能合约的动态同意管理系统,由区块链技术支持,针对通用数据保护条例下的个人数据使用。我们的以用户为中心的动态同意管理系统允许用户控制其个人数据的收集,并在整个数据生命周期中同意其使用。交易历史和日志记录在区块链中,提供可信的防篡改数据来源、问责制和可追溯性。我们设计并实现了系统的原型,以展示其可行性。通过实验测试和验证过程评估了系统的可接受性和可靠性。我们还分析了系统的安全性和隐私性,并评估了其性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/559b/8659597/7f2fc4d88807/sensors-21-07994-g001.jpg

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