TY - JOUR AU - Jones, Michael AU - Johnson, Matthew AU - Shervey, Mark AU - Dudley, Joel T AU - Zimmerman, Noah PY - 2019 DA - 2019/08/14 TI -使用区块链进行特征工程的隐私保护方法:审查、评估和概念证明乔- J地中海互联网Res SP - e13600六世- 21 - 8 KW -隐私KW -机器学习KW -保密KW -数据收集KW -移动健康KW -特性工程KW -地理位置KW -区块链KW -智能合同KW -密码学KW -可信执行环境AB -背景:私人数据的保护是一个关键的责任研究,收集研究参与者的身份信息。限制数据收集的范围和防止数据的二次使用是管理这些风险的有效策略。一个理想的数据收集框架应该包括特征工程，在一个没有可信第三方的安全环境中，从敏感的原始数据中提取次要特征的过程。目的:本研究旨在比较当前的方法，基于他们如何维护数据隐私和他们的实现的实用性。这些方法包括依赖可信第三方的传统方法，以及加密、安全硬件和基于区块链的技术。方法:定义一组属性来评估每种方法。在此基础上进行了定性比较。每种方法的评估都以共享生物医学研究地理位置数据的用例为框架。结果:我们发现，依靠可信第三方来保护参与者隐私的方法，并不能提供足够有力的保证，确保敏感数据不会暴露在现代数据生态系统中。 Cryptographic techniques incorporate strong privacy-preserving paradigms but are appropriate only for select use cases or are currently limited because of computational complexity. Blockchain smart contracts alone are insufficient to provide data privacy because transactional data are public. Trusted execution environments (TEEs) may have hardware vulnerabilities and lack visibility into how data are processed. Hybrid approaches combining blockchain and cryptographic techniques or blockchain and TEEs provide promising frameworks for privacy preservation. For reference, we provide a software implementation where users can privately share features of their geolocation data using the hybrid approach combining blockchain with TEEs as a supplement. Conclusions: Blockchain technology and smart contracts enable the development of new privacy-preserving feature engineering methods by obviating dependence on trusted parties and providing immutable, auditable data processing workflows. The overlap between blockchain and cryptographic techniques or blockchain and secure hardware technologies are promising fields for addressing important data privacy needs. Hybrid blockchain and TEE frameworks currently provide practical tools for implementing experimental privacy-preserving applications. SN - 1438-8871 UR - //www.mybigtv.com/2019/8/e13600/ UR - https://doi.org/10.2196/13600 UR - http://www.ncbi.nlm.nih.gov/pubmed/31414666 DO - 10.2196/13600 ID - info:doi/10.2196/13600 ER -