EAGER: SARE: In-Sensor Hardware-Software Co-design Methodology of the Hall Effect Sensors to Prevent and Contain the EMI Spoofing Attacks in the Analog-RF Systems

该项目将创建一种新颖的传感器内防御方法，使最先进的霍尔传感器能够抵御外部电磁干扰（EMI）欺骗攻击。文献中先前的工作仅关注模拟射频电子设备的安全性，使其在设备级对EMI具有鲁棒性。然而，很少有人关注与模拟射频电子紧密连接的模拟传感器（例如霍尔传感器）的安全性。如今，许多模拟射频电子设备都集成了不同的板载霍尔传感器。因此，来自非常规攻击的安全威胁可能伴随着机载霍尔传感器的emi欺骗，并且这种攻击可能传播到连接的模拟rf电子设备，从而阻碍整个系统的完整性。例如，已经证明，利用外部磁场欺骗太阳能逆变器的霍尔传感器的攻击可以故意扰乱电网频率，电压，并注入虚假的实功率或无功功率来破坏电力系统。类似的攻击也可能发生在其他关键系统中，因为板载霍尔传感器由于其低成本、高线性度和准确性，如今在各种RF应用（例如，自动驾驶汽车、智能电网、机器人、工业工厂、导弹制导和军事防御）中普遍存在。因此，研究界需要解决这样一个重要的安全挑战。本课题将对模拟射频系统的安全性和防伪设计产生重大影响。该项目的成果将通过出版物和演讲传播给包括学术界、工业界和政府在内的更广泛的社区。此外，拟议的研究活动的结果将纳入课程作业和其他教育活动。仅使模拟射频电子稳健可能无法有效确保连接系统的安全性，以防止通过板载模拟霍尔效应传感器进行外部EMI欺骗攻击。本研究将开发一种新颖的传感器内嵌入式核心的软硬件架构。传感器内嵌入式核心将霍尔传感器与数字信号处理（DSP）核心集成，使用传感器内存储器块外设，以保持连接的模拟rf系统的安全性。检测EMI欺骗攻击至关重要，在受到攻击时保持连接的RF系统正常运行更为重要。在提出的架构中，嵌入在单个霍尔传感器中的三个等距霍尔元件将用于检测和测量任何类型的外部EMI欺骗攻击。将开发一种新的算法，通过使用FPGA和DSP核心两个不同的平台，分别完成两种不同类型的任务（时间敏感处理任务和面向控制的任务），将外部EMI欺骗数据从原始信号数据中分离出来。FPGA和DSP核心之间的通信将使用DMA （Direct-Memory-Access）来增加带宽。此外，所提出的方法将是低功耗的，并且不会妨碍连接的模拟射频系统的现有数据处理速度和数据速率。该技术既能检测外部电磁干扰欺骗攻击，又能实时抑制霍尔传感器内部的攻击，使攻击无法进一步传播到所连接的模拟射频系统。如果成功，这种方法可以进一步发展并应用于其他类型的模拟传感器。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 will create a novel in-sensor defense methodology to make the state-of-the-art Hall sensors robust against external Electromagnetic-Interference (EMI) spoofing attacks. Prior works in the literature focused only on the safety of the analog-RF electronics by making them robust against EMI in the device level. However, little attention has been paid on the security of analog sensors (e.g., Hall sensors) tightly connected to the analog-RF electronics. Nowadays, many analog-RF electronics are integrated with different onboard Hall sensors. Therefore, security threats from unconventional attacks may come with EMI-spoofing the onboard Hall sensors and such attacks may propagate to the connected analog-RF electronics, hampering the integrity of the whole system. For example, it has been demonstrated that an attack by spoofing the Hall sensors of the solar inverters using an external magnetic field can intentionally perturb the grid frequency, voltage, and inject false real or reactive power to disrupt the power system. Similar attacks may also happen in other critical systems as onboard Hall sensors are nowadays pervasive in various RF applications (e.g., autonomous vehicles, smart grids, robotics, industrial plants, missile guidance, and military defense) because of their low cost, high linearity, and acuracy. Therefore, the research community needs to solve such an important security challenge. This project will have a large impact on the safety and security design of analog-RF systems. The outcomes of this project will be disseminated to the broader communities involving academia, industry, and government via publications and presentations. Moreover, the results of the proposed research activities will be integrated into course work and other educational activities. Making only the analog-RF electronics robust may not be effective to ensure the security of connected systems against external EMI spoofing attacks through the onboard analog Hall effect sensors. This research will develop a novel hardware-software architecture of in-sensor embedded core. The in-sensor embedded core will integrate the Hall sensors with Digital Signal Processing (DSP) cores using the in-sensor memory block peripherals to keep the connected analog-RF systems safe and secure. Detecting an EMI spoofing attack is critical and it is even more critical to keep the connected RF systems operating properly while under an attack. In the proposed architecture, three equidistant Hall elements embedded in a single Hall sensor will be used to detect and measure any type of external EMI spoofing attack. A novel algorithm will be developed to separate the external EMI spoofing data from the original signal data by using two different platforms, namely the FPGA and the DSP core, to accomplish two different types of tasks (time-sensitive processings tasks and control-oriented tasks) respectively. The communication between the FPGA and the DSP core will use the Direct-Memory-Access (DMA) to increase the bandwidth. Moreover, the proposed methodology will be low-power and will not hamper the existing data-processing speed and data rates of the connected analog-RF systems. This technique not only detects the external EMI spoofing attack but also contains the attacks inside the Hall sensors in real time, so that the attacks cannot propagate further to the connected analog-RF systems. If successful, this methodology can be further developed and applied to other types of analog sensors.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.