QoIA-Aware Attack Resilient Database Systems

QoIA 感知攻击弹性数据库系统

• 批准号: 0233324
• 负责人: Peng Liu
• 金额: --
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0233324&HistoricalAwards=false
• 关键词: QoIA; Aware; Attack; Resilient; Database

This project will build a QoIA-aware attack resistant databasesystem framework, call Linba. The trustworthiness of a computingsystem in delivering valid services in face of attacks hasbecome a more critical concern than ever as people are experiencingincreased cyber security threats. A Quality of InformationAssurance (QoIA) service is a service associated with a specific levelof trustworthiness. From the viewpoint of end users, the goal of trustedcomputing is to enable people to get the QoIA services that theyhave subscribed for even in face of attacks. However, (most) existingtrusted systems cannot deliver QoIA services since they have very limitedability in providing (sustained) quantitative trustworthiness guarantees.The objective of this research is to build a new trusted computinginfrastructure that is able to continue delivering QoIA servicesin face of attacks and cost constraints. Based on a novel formal(service) trustworthiness model, Linbadelivers multilevel, differential, quantitative QoIA servicesthrough near optimal neuro-fuzzy composite QoIA adaptations whereLinba intelligently adapts itself to environment changes andQoIA-cost tradeoffs are done in an optimized way. Successfuldevelopment of Linba will arm existing trusted database systemswith the ability to deliver QoIA services (in a cost-effectiveway) and provide very valuable hints on developing a variety of othertypes of trusted computing systems that can deliver QoIA services.The cost-effectiveness of Linba will be evaluated throughsimulation or prototyping.

该项目将构建一个支持qoia的抗攻击数据库系统框架，称为Linba。随着人们面临越来越多的网络安全威胁，计算系统在面对攻击时提供有效服务的可信度已经成为一个比以往任何时候都更加重要的问题。信息质量保证（QoIA）服务是与特定级别的可信度相关联的服务。从最终用户的角度来看，可信计算的目标是使人们即使在受到攻击的情况下也能获得他们所订阅的QoIA服务。然而，（大多数）现有的可信系统不能提供QoIA服务，因为它们在提供（持续的）定量可信度保证方面非常有限。本研究的目的是建立一个新的可信计算基础设施，能够在面对攻击和成本限制的情况下继续提供QoIA服务。基于一种新颖的形式（服务）可信度模型，linba通过近最优神经模糊复合QoIA自适应提供多层次、差异化、定量的QoIA服务，其中linba智能地适应环境变化，并以优化的方式进行QoIA成本权衡。Linba的成功开发将使现有的可信数据库系统具备交付QoIA服务的能力（以一种经济有效的方式），并为开发能够交付QoIA服务的各种其他类型的可信计算系统提供非常有价值的提示。Linba的成本效益将通过模拟或原型来评估。