Privacy-Preserving Collaborative Analytics on Sensitive Data

对敏感数据进行隐私保护协作分析

• 批准号: LP220200649
• 负责人: Prof Xun Yi
• 金额: $ 22.95万
• 依托单位: RMIT University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP220200649
• 关键词: Privacy; Preserving; Collaborative; Analytics; Sensitive

This project aims to develop efficient solutions that allow multiple institutes to carry out collaborative analytics on aggregated data without revealing their sensitive data to each other. The project expects to remedy acute privacy concerns when institutes share sensitive data across boundaries for collective insights. The expected outcomes include a hybrid trust model with distributed trusts to provide malicious security guarantees, lightweight privacy-enhancing techniques to express rich analytical functionalities, and a system platform for real-world applications. This should provide significant benefits such as facilitating industries to safeguard their customers' data and uplift their businesses in a secure and trustworthy fashion.

该项目旨在开发高效的解决方案，允许多个机构对汇总数据进行协作分析，而不会相互泄露敏感数据。该项目希望在机构跨界共享敏感数据以获得集体见解时解决严重的隐私问题。预期的成果包括一个混合信任模型与分布式信任提供恶意的安全保证，轻量级的隐私增强技术，以表达丰富的分析功能，并为现实世界的应用程序的系统平台。这将带来巨大的好处，例如促进行业以安全和值得信赖的方式保护其客户数据并提升其业务。