MRI: Development of An Instrument for Secure Cyber Physical Systems Analytics

该项目旨在开发一种安全且可扩展的仪器，可以有效地对从物联网（IoT）设备收集的数据进行大数据分析，同时提供保护数据安全和隐私的工具。物联网设备是通过使用互联网收集、处理和传输数据来监测和控制与物理世界交互的系统。物联网设备包括家庭自动化系统、智能电网、交通系统、医疗设备、建筑控制、制造和工业控制系统。随着物联网设备部署的增加，这些设备产生的数据量也在增加。因此，需要大规模和安全的数据处理系统来处理和提取信息，以进行有效和有影响力的决策。当物联网数据包含敏感信息时，计算和数据安全中的可信度问题就会出现。例如，使用无线血压监测仪等家庭健康设备收集的数据可能需要进行分析，并与其他信息相关联。在这些情况下，数据所有者可能需要保护他们的数据，并要求保证数据的安全性和完整性。该仪器的开发将使需要高效和安全处理物联网数据的新研究项目成为可能。因此，这可能允许创建新的物联网数据处理工具和服务，这些工具和服务由于安全和隐私问题而在今天是不可行的。拟议的工具将以一种新颖和独特的方式整合两个重要组成部分。首先，将开发可以从工业物联网（IIoT）设备等物联网设备收集各种数据的物联网数据收集组件。该组件将创建仪器的必要数据收集部分。它将允许研究人员调整数据收集频率和粒度，以便为各种研究项目提供不同类型的数据收集活动。仪器的第二个组件将是安全数据分析层，可以处理潜在的敏感物联网数据，包括网络数据包、传感器数据等。作为该组件的一部分，将实现最近开发的利用可信执行环境（tee）的安全数据处理技术。此外，这些基于tee的技术将针对不同类型的物联网数据进行定制，以提高效率并限制任何敏感数据泄漏。在这个项目中，这些组件将使用定制开发的软件进行集成，这些软件将在最后阶段开放源代码。此外，这些组件将被集成，以测试各种研究工具的可扩展性，安全性和数据隐私。开发的仪器将提供给我们的合作者和更大的科学界。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to develop a secure and scalable instrument that can efficiently perform big data analytics on data collected from Internet of Things (IoT) devices while providing tools for preserving data security and privacy. IoT devices are monitoring and controlling systems that interact with the physical world by collecting, processing and transmitting data using the internet. IoT devices include home automation systems, smart grid, transportation systems, medical devices, building controls, manufacturing and industrial control systems. With the increase in deployment of IoT devices, the amount of data generated by these devices also increases. There is thus a need for large-scale, and secure data processing systems to process and extract information for efficient and impactful decision-making. The issue of trustworthiness in computation and data security arises when the IoT data contains sensitive information. For example, data collected using the home health devices such as a wireless blood-pressure monitor may need to be analyzed and correlated with other information. In these cases, data owners may need to protect their data and demand guaranties about data security and integrity. Development of this instrument will enable new research projects that require efficient and secure processing of IoT data. Consequently, this may allow the creation of novel IoT data processing tools and services which are not feasible today due to security and privacy concerns. The proposed instrument will integrate two important components in a novel and unique way. First, an IoT data gathering component that can collect various data from IoT devices including the industrial IoT (IIoT) devices, will be developed. This component will create the necessary data gathering part of the instrument. It will allow researchers to adjust data collection frequency and granularity to enable different types of data collection activities for various research projects. The second component of the instrument will be the secure data analytics layer that can process the potentially sensitive IoT data including the network packets, sensor data, etc. As part of this component, recently developed secure data processing techniques which leverage trusted execution environments (TEEs) will be implemented. In addition, these TEE-based techniques will be tailored for different types of IoT data to increase their efficiency and limit any sensitive data leakage. During this project, these components will be integrated using custom developed software which will be open sourced at the final stage. Furthermore, these components will be integrated to test various research tools with respect to scalability, security and data privacy. The developed instrument will be made available to our collaborators and larger scientific community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.