Autonomic Middleware for Self-protection, Data Transfers, and Anomaly Analytics as a Service

用于自我保护、数据传输和异常分析即服务的自主中间件

• 批准号: 1032038
• 负责人: Jose Fortes
• 金额: $ 13.5万
• 依托单位: University of Florida
• 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: 2010-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1032038&HistoricalAwards=false
• 关键词: Autonomic; Middleware; Self; protection; Data

This proposal seeks funding for the Center for Autonomic Computing (CAC) studies conducted by the University of Florida site (lead) and the University of Arizona site. Funding Requests for Fundamental Research are authorized by an NSF approved solicitation, NSF 10-507. The solicitation invites I/UCRCs to submit proposals for support of industry-defined fundamental research. This project proposal focuses on autonomic computing and systems, applicable to the important areas of security, fault management, and data centers. Planned are the prototypes to be deployed on test bed environments driven by the requirements from industry. The most interesting part of the proposal are applications to SCADA environments, which integrate monitoring, multi-level behavior analysis, decision fusion and risk analysis relative to security of SCADA environments. Other areas include autonomic peer-to-peer systems, as well as study related to the data centers, both at the application layer and data center hardware, where focus is on robustness.The successful completion of this project will represent a significant step toward the design and deployment of highly secure SCADA systems and networks. In addition to security, the autonomic detection of anomalies in applications or subsystems of a datacenter addresses inefficiencies in data center design by eliminating the dependence on over-provisioning, which is a resource-inefficient strategy for ensuring quality of service by trying to offset any sub-system failures and malfunctions. The project has also potential for broader impact on data-intensive applications that leverage the availability of ad-hoc desktop grids for high-throughput computing.

该提案为佛罗里达大学网站（牵头）和亚利桑那大学网站进行的自主计算中心（CAC）研究寻求资金。基础研究的资助申请由 NSF 批准的征集 NSF 10-507 授权。 此次征集邀请 I/UCRC 提交支持行业定义的基础研究的提案。 该项目提案重点关注自主计算和系统，适用于安全、故障管理和数据中心等重要领域。计划将原型部署在由行业需求驱动的测试台环境中。该提案最有趣的部分是在 SCADA 环境中的应用，它集成了与 SCADA 环境安全相关的监控、多级行为分析、决策融合和风险分析。其他领域包括自主点对点系统，以及与数据中心相关的研究，包括应用层和数据中心硬件，重点是鲁棒性。该项目的成功完成将代表着向高度安全的 SCADA 系统和网络的设计和部署迈出了重要一步。除了安全性之外，数据中心应用程序或子系统中的异常自动检测还可以消除对过度配置的依赖，从而解决数据中心设计中的低效率问题，过度配置是一种资源效率低下的策略，通过尝试抵消任何子系统故障和故障来确保服务质量。该项目还可能对利用临时桌面网格进行高吞吐量计算的数据密集型应用程序产生更广泛的影响。