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

本研究探讨保护计算的完整性和增强数据隐私的分布式计算平台上执行的应用程序，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主管提供针对应用程序和平台特定约束的可量化保护和隐私机制。该项目考虑了现有的平台，禁止参与计算机（“参与者”）与其他参与者进行通信，以及潜在的未来分层平台，允许参与者之间的通信，并允许平台拓扑结构的动态变化。计算完整性问题的解决方法包括概率验证和人工智能机制的新应用，用于检测异常行为。数据隐私的方法是基于模糊数据值，同时保持足够的输出信息，用于从庞大的数据集中识别特定的重要数据。实验研究链接到教育在里士满大学通过特殊主题课程的开发和现有课程的增强，并通过研究奖学金，设备和旅行项目相关的会议和研讨会的资金，从事相关研究的本科生。该项目的成果将提供更安全的计算平台，促进科学家和从业人员之间的跨学科研究。受益于这项研究成果的具体领域包括生物学，化学，数学，金融，医学和进化论。项目的执行将修改现有的开放源码分布式计算代码，并将通过项目网址（http：//dvc.richmond.edu/）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/).