NSF DSSP Workshop: Data Science for Secure and Privacy-Aware Big Data Management and Mining

NSF DSSP 研讨会：用于安全和隐私意识大数据管理和挖掘的数据科学

• 批准号: 1647860
• 负责人: Feifei Li
• 金额: $ 9.8万
• 依托单位: University of Utah
• 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: 2016-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1647860&HistoricalAwards=false
• 关键词: NSF; DSSP; Workshop; Data; Science

In the era of big data, across numerous application domains, large amounts of data are being collected, integrated, and analyzed to support rich application semantics and enable data-driven science discovery. While having the access to more data leads to more opportunities for analytics, mining, learning, and knowledge discovery, at the same time, it also increases the chance of security breach and privacy infringement. In essence, adversaries are able to gain more insights into an application or system, and equipped with more background knowledge, when more (relevant) data are made available to him/her. This award supports the organization of a workshop to bring together researchers and practitioners from different sub-fields of data science and security/privacy to discuss the vision, challenges, and opportunities for the protection of security and privacy in big data management and mining.The agenda of the workshop has broader impacts on the scientific communities and the society at large by identifying the challenges for data science research related to security and privacy, and foster the vision for secure and privacy-aware data management and mining through an interdisciplinary data science approach. More specifically, the workshop increases the interactions among several related communities, including cryptography, database and data management, mining and learning, systems, social and behavior sciences, and applied security.

在大数据时代，在众多应用领域中，正在收集，集成和分析大量数据，以支持丰富的应用程序语义并启用数据驱动的科学发现。同时，在获得更多数据的同时，还带来了更多的分析，采矿，学习和知识发现的机会，但同时也增加了安全漏洞和侵犯隐私的机会。从本质上讲，当对手能够获得更多（相关）数据时，对手能够对应用程序或系统获得更多的见解，并配备更多的背景知识。该奖项支持组织研讨会的组织，以将来自数据科学和安全/隐私的不同子领域的研究人员和从业人员汇集在一起​​，讨论在大数据管理和采矿中保护安全和隐私的愿景，挑战和机会。研讨会的议程对数据的挑战和挑战，以及对数据的挑战和挑战的挑战，以及对数据的挑战，以及对数据的挑战的更广泛的影响，并将通过跨学科数据科学方法开采。更具体地说，研讨会增加了几个相关社区之间的互动，包括密码学，数据库和数据管理，采矿和学习，系统，社会和行为科学以及应用安全性。