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: 1547358
• 负责人: Elisa Bertino
• 金额: $ 27.91万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547358&HistoricalAwards=false
• 关键词: CICI; Data; Provenance; Collaborative; Research

Today scientists in many disciplines, including biology, medicine, agronomy, energy management, hydrology, and earth sciences, rely on the use of massive datasets collected from various sources. Such collections are made possible by advances in computer technology such as sensors which collect data such as humidity, air quality and so forth, and powerful computer systems that analyze the data. The increased use of data for scientific research poses some important challenges. Data can have errors which impact conclusions derived from the data. Scientific research has to be reproducible to support validation and detection of scientific misconduct. Addressing these challenges requires tracking data used in research projects. Examples include: tracking the source that originated the data ? for example a mobile phone that acquired some images- and its geographic location; tracking which computer systems processed the data; tracking how scientists modified given data. Such a set of information is referred to as provenance ? very much like the provenance of artistic artifacts. Managing provenance is technically complex; yet it is key for data-intensive research. This project makes important advances in this direction by developing software systems for securely managing provenance. This project develops a provenance management system for cyberinfrastructure that includes different types of hosts, devices, and data management systems. The proof-of-concept system, referred to as Cyber-provenance Infrastructure for Sensor-based Data-Intensive Research (CY-DIR), will support scientists throughout the life-cycle of their sensor-based data collection processes, including the continuous monitoring of sensors to ensure that provenance is collected and recorded, and the traceable use and processing of the data across different data management systems. CY-DIR provides researchers with provenance and metadata about data being collected by sensors. Provenance security will be assured by the use of efficient encryption techniques for use in sensors, secure logging techniques, and secure processors. Research from this project will provide novel results in several areas: provenance techniques for sensor data; cryptographic key management for sensors, mobile devices, and unmanned aircraft systems; provenance aware streaming data processing techniques; protection of provenance data against tempering; provenance data integration across different data management systems.

今天，许多学科的科学家，包括生物学、医学、农学、能源管理、水文学和地球科学，都依赖于从各种来源收集的大量数据集的使用。计算机技术的进步使这种收集成为可能，例如收集湿度、空气质量等数据的传感器，以及分析数据的强大计算机系统。越来越多的数据用于科学研究带来了一些重要的挑战。数据可能存在错误，从而影响从数据得出的结论。科学研究必须是可重现的，以支持对科学不端行为的验证和发现。应对这些挑战需要跟踪研究项目中使用的数据。例如：跟踪数据的来源？例如，一部手机获取了一些图像及其地理位置；跟踪哪些计算机系统处理了数据；跟踪科学家如何修改给定的数据。这样的一组信息被称为来源？就像艺术品的起源一样。管理来源在技术上是复杂的；但对于数据密集型研究来说，这是关键。该项目通过开发安全管理产地的软件系统，在这方面取得了重要进展。该项目为网络基础设施开发了一个来源管理系统，其中包括不同类型的主机、设备和数据管理系统。概念验证系统被称为基于传感器的数据密集型研究的网络来源基础设施(CY-DIR)，将在科学家基于传感器的数据收集过程的整个生命周期中为科学家提供支持，包括对传感器的持续监测以确保收集和记录来源，以及跨不同数据管理系统对数据的可追溯性使用和处理。CY-DIR为研究人员提供了关于传感器收集的数据的来源和元数据。通过使用用于传感器的高效加密技术、安全日志记录技术和安全处理器，将确保来源安全。该项目的研究将在几个领域提供新的成果：传感器数据的来源技术；传感器、移动设备和无人驾驶飞机系统的密钥管理；来源感知流数据处理技术；来源数据防止篡改；来源数据跨不同数据管理系统的集成。