CT-ISG/RUI: Ensuring Computation Integrity in Distributed Volunteer Computing Platforms

这项研究调查了在分布式计算平台上执行的应用程序的计算完整性保护和数据隐私增强，这些应用程序利用连接到互联网的计算机的空闲处理器周期。该项目的目标是为计算监督者提供可量化的保护和隐私机制，以适应特定于应用程序和平台的限制。该项目考虑了禁止参与计算机(“参与者”)与其他参与者通信的现有平台，以及允许参与者之间通信并允许动态变化平台拓扑结构的潜在未来分层平台。解决计算完整性问题的方法包括概率验证和人工智能机制的新应用，以检测异常行为。数据隐私的方法基于模糊数据值，同时保持足够的输出信息，以便从海量数据集中识别特定的重要数据。实验研究通过开发专题课程和加强现有课程，以及通过资助研究金、设备和旅行参加与项目有关的会议和讲习班，使本科生参与相关研究，从而与里士满大学的教育相联系。该项目的成果将提供进入更安全的计算平台的途径，促进科学家和从业人员进行跨学科研究。受益于这项研究结果的具体领域包括生物、化学、数学、金融、医学和进化论。项目实施将修改现有的开源分布式计算代码，并将通过项目网站(http://dvc.richmond.edu/).)进行传播

This research investigates the protection of computation integrity and enhancement of data privacy for applications executed on distributed computing platforms that utilize the spare processor cycles of computers connected to the Internet. The goal of the project is to provide computation supervisors with quantifiable protection and privacy mechanisms tailored to application and platform specific constraints. The project considers existing platforms, which prohibit participating computers ("participants") from communicating with other participants, as well as potential future hierarchical platforms that permit communication among participants and allow dynamic variation of platform topology. The approach to the problem of computation integrity consists of probabilistic verification and novel application of artificial intelligence mechanisms for detecting anomalous behavior. The approach to data privacy is based on obscuring data values while maintaining sufficient output information for identifying specific important data from among a vast data set. The experimental research links to education at the University of Richmond through development of special topics courses and enhancement of existing courses, and by engaging undergraduates in relevant research via funding of research fellowships, equipment, and travel to project related conferences and workshops. The results of the project will provide access to more secure computing platforms, fostering inter-disciplinary research among scientists and practitioners. Specific fields benefiting from results of this research include biology, chemistry, math, finance, medicine, and evolutionary theory. Project implementations will modify existing open source distributed computing code and will be disseminated via the project Web site (http://dvc.richmond.edu/).