SaTC: CORE: Medium: Collaborative: Privacy-Aware Trustworthy Control as a Service for the Internet of Things (IoT)

物联网（IoT）包括各种设备，如智能家电、汽车和其他物理系统，这些设备深深嵌入我们的日常生活中，并面临黑客或国家行为者对安全和隐私的新型威胁。在IoT系统中，传感器用于探测系统的物理状态（例如，建筑物中的温度或汽车车轮的旋转速度），然后软件控制系统使用算法来确定对系统的适当调整（例如，运行空调5分钟或踩刹车）。该项目的重点是保护这些控制系统和算法，以确保用户的安全和隐私。该研究通过从控制，密码学，软件和硬件中提取的机制来解决物联网的可信和隐私感知控制架构。其中包括：（i）用于结合物理世界的动态模型和相关联的感测和致动通道对控制软件的安全和隐私属性进行形式化推理的框架;（ii）轻量级域特定机制，用于通过软件应用程序对信息流进行监管，同时利用机器学习和控制算法的语义、系统的物理和数值属性;（iii）通过原则性传感器数据扰动、针对加密数据上的有效计算而优化的控制算法、以及被定制为保护感测数据和控制算法参数的硬件支持的可信计算基础的组合来强制执行期望的安全和信息泄漏属性;（iv）弹性控制和定时基础设施，通过混合使用边缘和云资源以及物理模型来防止对定时信息的攻击。这些机制的成功正在智能家居、工业自动化和智能汽车的实验测试平台上进行评估，但对许多其他物联网应用具有更广泛的适用性。该项目团队还通过加州大学洛杉矶分校的洛杉矶计算圈计划，为高中生创建了一个新的物联网安全研究生课程，并开发了物联网安全教育材料。

The Internet of Things (IoT) includes a variety of devices such as smart appliances, cars, and other physical systems that are deeply embedded in our everyday lives and that are at risk from new kinds of threats to security and privacy from hackers or state actors. In IoT systems, sensors are used to probe the physical state of the system (e.g., temperature in a building or rotational speed of a wheel of a car) and then software control systems use algorithms to determine appropriate adjustments to the system (e.g., run the air conditioning for 5 minutes or apply the brakes). The project is focused on protecting those control systems and algorithms to ensure security and privacy for users.The research addresses trustworthy and privacy-aware control architectures for IoT through mechanisms drawn from control, cryptography, software, and hardware. These include: (i) A framework for formally reasoning about safety and privacy properties of control software in conjunction with dynamical models of the physical world and associated sensing and actuation channels; (ii) Lightweight domain-specific mechanisms, for policing flow of information through software applications, while leveraging the semantics of machine learning and control algorithms, physics of the system, and numerical properties; (iii) Enforcing desired safety and information leakage properties via a combination of principled sensor data perturbation, control algorithms optimized for efficient computation over encrypted data, and a hardware-supported trusted computing base tailored to protecting sensed data and control algorithm parameters; (iv) A resilient control and timing infrastructure that protects against attacks on timing information through a hybrid use of edge and cloud resources and physical models. The success of the mechanisms is being assessed on experimental testbeds for smart home, industrial automation and smart vehicles, but have broader applicability to many other IoT applications. The project team is also creating a new graduate class on IoT security and developing educational material on IoT security for high-schoolers through the Los Angeles Computing Circle initiative at the University of California - Los Angeles.