TC: Medium: Security and Privacy Preserving Data Mining and Management for Disctributed Domains

TC：中：分布式域的安全和隐私保护数据挖掘和管理

• 批准号: 0964639
• 负责人: Arif Ghafoor
• 金额: $ 119.29万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-15 至 2018-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0964639&HistoricalAwards=false
• 关键词: TC; Medium; Security; Privacy; Preserving

A fundamental but challenging issue in information security is secure sharing and management of sensitive data and information among numerous organizations that form large-scale e-enterprises. Today, an increasing number of enterprises are using the Internet for managing and sharing users? and enterprise information through online databases. However, security and privacy of data is an overriding concern currently limiting the proliferation of information technology. Among others, the two key security issues are; (a) interoperability challenge of diverse security policies exercised by collaborating organizations for sharing sensitive information and; (b) using collaborative knowledge for detecting and responding to any emerging security or emergency threats. The objective of this project to develop a scalable multi-domain information security framework which: (a) facilitates large-scale integration, mining, and analysis of multimedia data residing in multiple domains for identifying sensitive information that require controlled dissemination (b) allows distributed real-time content analysis of multimedia data streams across multiple-domains for correlating detectable events, (c)l provides integration and evolution of inter-domain access control policies for distributed multimedia applications, and (d) ensures protection of user?s information. The project uses several innovative approaches to meet these objectives. First, novel real-time data mining and stream-correlation methods is used for extracting useful content and detecting events embedded in data streams by using multiple sliding window operators. Second, an efficient privacy/security based multimedia data clustering mechanism allows a prevailing security policy to be adaptable to the changing context and the datasets. The uniqueness of this approach is the adaptive nature of security policies. In addition, a novel XML-based integrated mechanism is used for encoding of multimedia data in conjunction with multi-domain security policies for ensuring technical viability and portability of the system.The proposed research is expected to have direct and long-term impact on developing secure information infrastructures, such as e-commerce, digital libraries, and healthcare systems, which are projected to have an important role at a global scale for the next several decades. The research results can help in alleviating the heavy financial risks associated with information and system security and in general, meeting the national information infrastructure security needs and threat management. The research will be pursued in collaboration with Cyber Center, the Center for Education and Research in Information Assurance and Security (CERIAS) and PURVAC facilities at Purdue University with which the PI?s have strong affiliation and on-going collaboration. Results and tools developed will be made available over the Web to research community. In The team has a track record of providing their research results and tools to various research communities in the areas of multimedia databases and information security management.For further information see the project web site at theURL: http://cobweb.ecn.purdue.edu/~dmultlab/ http://cobweb.ecn.purdue.edu/%7Edmultlab/

信息安全中的一个基本但具有挑战性的问题是构成大型电子企业的众多组织之间敏感数据和信息的安全共享和管理。如今，越来越多的企业使用互联网来管理和共享用户？通过在线数据库获取企业信息。然而，数据的安全和隐私是当前限制信息技术扩散的首要问题。其中，两个关键的安全问题是： (a) 合作组织为共享敏感信息而采取的各种安全政策的互操作性挑战； (b) 利用协作知识来检测和响应任何新出现的安全或紧急威胁。该项目的目标是开发一个可扩展的多域信息安全框架，该框架：（a）促进驻留在多个域中的多媒体数据的大规模集成、挖掘和分析，以识别需要受控传播的敏感信息（b）允许跨多个域的多媒体数据流的分布式实时内容分析，以关联可检测的事件，（c）l提供域间访问控制策略的集成和演进 分布式多媒体应用程序，(d) 确保保护用户信息。 该项目使用多种创新方法来实现这些目标。首先，新颖的实时数据挖掘和流关联方法用于通过使用多个滑动窗口运算符来提取有用内容并检测嵌入在数据流中的事件。其次，基于高效隐私/安全的多媒体数据集群机制允许流行的安全策略适应不断变化的上下文和数据集。这种方法的独特之处在于安全策略的适应性。此外，采用一种新颖的基于XML的集成机制结合多域安全策略对多媒体数据进行编码，以确保系统的技术可行性和可移植性。所提出的研究预计将对开发安全信息基础设施产生直接和长期的影响，例如电子商务、数字图书馆和医疗保健系统，预计这些基础设施将在未来几十年在全球范围内发挥重要作用。研究成果有助于缓解与信息和系统安全相关的重大金融风险，并总体上满足国家信息基础设施安全需求和威胁管理。 该研究将与网络中心、信息保障和安全教育与研究中心 (CERIAS) 以及普渡大学的 PURVAC 机构合作进行，PI 与这些机构有着密切的联系和持续的合作。开发的结果和工具将通过网络提供给研究界。该团队在多媒体数据库和信息安全管理领域向各个研究社区提供研究成果和工具方面有着良好的记录。有关更多信息，请参阅项目网站：http://cobweb.ecn.purdue.edu/~dmultlab/ http://cobweb.ecn.purdue.edu/%7Edmultlab/