CICI: UCSS: Blockchain Based Assured Open Scientific Data Sharing and Governance

CICI:UCSS:基于区块链的有保障的开放科学数据共享和治理

基本信息

  • 批准号:
    2115094
  • 负责人:
  • 金额:
    $ 49.97万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-07-15 至 2025-06-30
  • 项目状态:
    未结题

项目摘要

Despite being one of the key driving forces behind scientific discovery and playing a critical role for the well-being of our society as a whole, scientific data sharing remains an issue fraught with security and integrity risks. This is because certain restrictions on data usage (e.g., maintaining appropriate audit logs for the data modifications) must be enforced rigorously, which is difficult to accomplish with existing technologies in a seamless manner. The need to share scientific data while honoring usage restrictions, protecting data integrity, and capturing provenance for scientific repeatability requires development of new software tools that can support these capabilities across multiple organizations’ boundaries. The novel blockchain based data sharing system built as a part of this project may result in advancing the knowledge base on how to automatically balance the conflicting goals of security and integrity requirements and information sharing in the context of open scientific discovery process. This system in return can significantly increase volume and variety of data shared for research purposes across a broad range of disciplines, thereby directly addressing the NSF Big Idea on Harnessing the Data Revolution, by further advancing capabilities of modern cyberinfrastructure and fostering novel opportunities for interdisciplinary data-intensive research. Furthermore, by actively incorporating our research results into the curriculum development, at both undergraduate and graduate levels, we foster the next generation of interdisciplinary scientists in a new era for open data.To achieve the above stated goals, this project builds an innovative system where blockchain techniques are leveraged for assured scientific data sharing. First, the project develops a policy specification framework tailored for open science data sharing. Using this framework, scientists may easily specify any usage restriction (e.g., do not re-identify human subjects, do not modify data, notify us if the data is lost due to hacking). Later on, using the blockchain framework, these restrictions will be captured, and stored via smart contracts. One novel aspect of the proposed framework is that, using machine learning techniques, it can analyze the smart contract based provenance information to automatically detect potentially anomalous data modifications. To test the capabilities of our framework, the project uses a multi-sensor based data collection and data sharing project for understanding the impact of urban pollution as a case study.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
尽管科学数据共享是科学发现背后的关键驱动力之一,并对我们整个社会的福祉发挥着关键作用,但科学数据共享仍然是一个充满安全和完整性风险的问题。这是因为对数据使用的某些限制(例如,为数据修改维护适当的审计日志)必须严格地强制执行,这很难用现有技术以无缝的方式完成。 在遵守使用限制、保护数据完整性和捕获科学可重复性来源的同时共享科学数据的需求,需要开发新的软件工具,以支持跨多个组织边界的这些功能。作为该项目的一部分,构建了基于区块链的新型数据共享系统,这可能会推动知识库的发展,即如何在开放的科学发现过程中自动平衡安全性和完整性要求以及信息共享之间的冲突目标。作为回报,该系统可以显着增加用于广泛学科研究目的的数据共享的数量和种类,从而通过进一步提高现代网络基础设施的能力和促进跨学科数据密集型研究的新机会,直接解决NSF关于利用数据革命的大想法。此外,通过积极将我们的研究成果纳入本科和研究生课程开发,我们培养了开放数据新时代的下一代跨学科科学家。为了实现上述目标,该项目构建了一个创新系统,其中利用区块链技术确保科学数据共享。首先,该项目为开放科学数据共享量身定制了一个政策规范框架。使用这个框架,科学家可以很容易地指定任何使用限制(例如,不要重新识别人类受试者,不要修改数据,如果数据因黑客攻击而丢失,请通知我们)。 稍后,使用区块链框架,这些限制将被捕获,并通过智能合约存储。 所提出的框架的一个新颖方面是,使用机器学习技术,它可以分析基于智能合约的出处信息,以自动检测潜在的异常数据修改。为了测试我们的框架的能力,该项目使用了一个基于多传感器的数据收集和数据共享项目,以了解城市污染的影响作为案例研究。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
GINN: Fast GPU-TEE Based Integrity for Neural Network Training
Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT
  • DOI:
    10.48550/arxiv.2211.13708
  • 发表时间:
    2022-11
  • 期刊:
  • 影响因子:
    0
  • 作者:
    C. Akcora;Murat Kantarcioglu;Y. Gel;Baris Coskunuzer
  • 通讯作者:
    C. Akcora;Murat Kantarcioglu;Y. Gel;Baris Coskunuzer
SECAUCTEE: Securing Auction Smart Contracts using Trusted Execution Environments
SECAUCTEE:使用可信执行环境保护拍卖智能合约
  • DOI:
    10.1109/blockchain53845.2021.00069
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Desai, Harsh;Kantarcioglu, Murat
  • 通讯作者:
    Kantarcioglu, Murat
Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kiarash Shamsi;Friedhelm Victor;Murat Kantarcioglu;Y. Gel;C. Akcora
  • 通讯作者:
    Kiarash Shamsi;Friedhelm Victor;Murat Kantarcioglu;Y. Gel;C. Akcora
The Impact of Data Distribution on Fairness and Robustness in Federated Learning
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Murat Kantarcioglu其他文献

Enforcing Honesty in Assured Information Sharing Within a Distributed System
在分布式系统内确保信息共享中加强诚实性
  • DOI:
    10.1007/978-3-540-73538-0_10
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    37.3
  • 作者:
    Ryan Layfield;Murat Kantarcioglu;B. Thuraisingham
  • 通讯作者:
    B. Thuraisingham
Incentive and Trust Issues in Assured Information Sharing
有保证的信息共享中的激励和信任问题
Determining the Impact of Missing Values on Blocking in Record Linkage
确定缺失值对记录链接阻塞的影响
Analysis of heuristic based access pattern obfuscation
基于启发式的访问模式混淆分析
Fair Machine Learning under Limited Demographically Labeled Data
有限人口标记数据下的公平机器学习
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Mustafa Safa Ozdayi;Murat Kantarcioglu;Rishabh K. Iyer
  • 通讯作者:
    Rishabh K. Iyer

Murat Kantarcioglu的其他文献

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{{ truncateString('Murat Kantarcioglu', 18)}}的其他基金

Conference: SaTC 2.0 Workshop
会议:SaTC 2.0研讨会
  • 批准号:
    2310255
  • 财政年份:
    2023
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
RAPID: Collaborative: A Privacy Risk Assessment Framework for Person-Level Data Sharing During Pandemics
RAPID:协作:大流行期间个人级数据共享的隐私风险评估框架
  • 批准号:
    2029661
  • 财政年份:
    2020
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
ATD: Topological Data Analysis for Threat Detection
ATD:用于威胁检测的拓扑数据分析
  • 批准号:
    1925346
  • 财政年份:
    2019
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
MRI: Development of An Instrument for Secure Cyber Physical Systems Analytics
MRI:开发安全网络物理系统分析仪器
  • 批准号:
    1828467
  • 财政年份:
    2018
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
CICI: Data Provenance: Collaborative Research: CY-DIR Cyber-Provenance Infrastructure for Sensor-Based Data-Intensive Research
CICI:数据来源:协作研究:CY-DIR 用于基于传感器的数据密集型研究的网络来源基础设施
  • 批准号:
    1547324
  • 财政年份:
    2016
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
I-Corps: Secure Document Management in the Cloud
I-Corps:云中的安全文档管理
  • 批准号:
    1339941
  • 财政年份:
    2013
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
TWC: Medium: Collaborative Proposal: Policy Compliant Integration of Linked Data
TWC:媒介:协作提案:关联数据的政策合规集成
  • 批准号:
    1228198
  • 财政年份:
    2012
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
TC: Large: Collaborative Research: Privacy-Enhanced Secure Data Provenance
TC:大型:协作研究:隐私增强的安全数据来源
  • 批准号:
    1111529
  • 财政年份:
    2011
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Continuing Grant
TC: Small: Collaborative: Protocols for Privacy-Preserving Scalable Record Matching and Ontology Alignment
TC:小型:协作:隐私保护可扩展记录匹配和本体对齐协议
  • 批准号:
    1016343
  • 财政年份:
    2010
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Standard Grant
NeTS: Medium: Collaborative Research: A Comprehensive Approach for Data Quality and Provenance in Sensor Networks
NeTS:媒介:协作研究:传感器网络中数据质量和来源的综合方法
  • 批准号:
    0964350
  • 财政年份:
    2010
  • 资助金额:
    $ 49.97万
  • 项目类别:
    Continuing Grant

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CICI: UCSS: Maximizing Data Utility and Participant Privacy through Usable, Secure Data Workflows for Human-Centered AI Research
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CICI: UCSS: ScienceAccess: Enabling Zero-Trust Resource Access Management for Scientific Collaborations
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  • 批准号:
    2232911
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CICI: UCSS: SciAuth: Deploying Interoperable and Usable Authorization Tokens to Enable Scientific Collaborations
CICI:UCSS:SciAuth:部署可互操作和可用的授权令牌以实现科学协作
  • 批准号:
    2114989
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    2021
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    $ 49.97万
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