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TRUST AND PRIVACY PRESERVING COMPUTING PLATFORM FOR CROSS-BORDER FEDERATION OF DATA

TRUST AND PRIVACY PRESERVING COMPUTING PLATFORM FOR CROSS-BORDER FEDERATION OF DATA
用于跨境数据联合的信任和隐私保护计算平台
批准号:
10044493
负责人:
金额:
$45.23万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
翻译
由于我们生活在一个数据驱动的时代,跨学科、地理上分散的数据存储库的出现是不可避免的。事实上,这些存储库不一定符合现有的跨学科数据表示标准,也不一定属于任何数据联盟倡议,使它们无法使用,因为研究人员无法轻松访问这些数据。此外,在大多数情况下,这种交互中的完整性、隐私和安全性要么非常困难,要么不可能维护。为此,TRUSTEE旨在提供一个绿色、安全、可信和隐私意识的框架,该框架将聚合各种跨学科的数据存储库,如医疗保健、教育、能源、空间、汽车、跨境等,并考虑其他欧洲数据联合空间和跨国计划,如Gaia-X和EOSC。TRUSTEE将提供一个安全的设计框架,其中存储的数据是同态加密的,从而为研究人员提供i)在加密域中搜索和使用数据的能力,ii)以开放和公平的方式对数据进行统一和有意义的FAIR表示,iii)通过高级本体进行复杂和上下文感知的查询,iv)通过透明可信的ML工作流进行数据处理和分析,通过直观的人工智能游戏场,这将通过利用最先进的方法和范例来促进人工智能的可解释性,互操作性和可重用性,v)遵守欧洲隐私和道德框架,例如,GDPR、PIA等,vi)通过应用同态加密层来实施隐私,所有数据交互都将通过该层进行,vii)基于区块链的交易记录器以确保问责制。TRUSTEE的完全加密解决方案将通过支持GAIA-X、EOSC、EGI等的六个不同用例进行验证,展示一个多学科、泛欧联合的FAIR和私有数据生态系统。
英文摘要
As we live in a data-driven era, the emergence of interdisciplinary, geographically dispersed, data repositories, is inevitable. The fact that these repositories do not necessarily abide with existing interdisciplinary data representation standards, nor do they necessarily belong to any data federation initiative, renders them unusable, since researchers cannot easily access this data. Moreover, most of the times, integrity, privacy, and security in such interactions is either very difficult, or impossible to maintain. Towards this end, TRUSTEE aims to bring a green, secure, trustworthy, and privacy-aware framework that will aggregate various interdisciplinary data repositories, such as Healthcare, Education, Energy, Space, Automotive, Cross-border etc. and also consider other European data federation spaces and trans-national initiatives, such as Gaia-X and EOSC. TRUSTEE will offer a secure-by-design framework, wherein stored data is homomorphically encrypted, thus offering researchers i) ability to search and use data in the encrypted domain, ii) a unified and meaningful FAIR representation of data, in an open and fair manner, iii) complex and context-aware queriesthrough advanced ontologies, iv) data processing and analysis through transparent trustworthy ML workflows, over an intuitive AI playground, which will promote AI eXplainability, interoperability, and re-usability, by utilizing state of the art methods and paradigms, v) compliance with European privacy and ethical frameworks, e.g., GDPR, PIA, etc., vi) enforce privacy by applying a Homomorphic encryption layer, through which all data interaction will take place, vii) a blockchain-based transaction recorder to ensure accountability. TRUSTEE's fully encrypted solution will be validated through six different use cases supporting GAIA-X, EOSC, EGI, etc. demonstrating a multi-disciplinary, Pan European federated FAIR and private data ecosystem.
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