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

EAGER：SARE：霍尔效应传感器的传感器内硬件-软件协同设计方法，用于防止和遏制模拟射频系统中的 EMI 欺骗攻击

• 批准号: 2028269
• 负责人: Mohammad Al Faruque
• 金额: $ 30万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028269&HistoricalAwards=false
• 关键词: EAGER; SARE; Sensor; Hardware; Software

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.

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。文献中的先前工作仅关注模拟RF电子器件的安全性，使其在器件级抗EMI。然而，很少关注模拟传感器的安全性（例如，霍尔传感器）紧密连接到模拟RF电子设备。如今，许多模拟RF电子器件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EMI欺骗板载霍尔传感器，并且这种攻击可能传播到连接的模拟RF电子器件，从而阻碍整个系统的完整性。例如，已经证明，通过使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动电网频率、电压，并注入虚假的真实的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如今在各种RF应用中普遍存在（例如，自动驾驶车辆、智能电网、机器人、工业工厂、导弹制导和军事防御），因为它们的低成本、高线性度和精确度。因此，研究界需要解决如此重要的安全挑战。该项目将对模拟射频系统的安全和保密设计产生重大影响。该项目的成果将通过出版物和演示文稿传播给学术界、工业界和政府等更广泛的群体。此外，拟议研究活动的结果将纳入课程工作和其他教育活动。仅使模拟RF电子器件坚固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的外部EMI欺骗攻击。本研究将发展一种新颖的感测器内嵌入式核心的软硬件架构。 内置传感器嵌入式内核将霍尔传感器与数字信号处理（DSP）内核集成在一起，使用内置传感器存储块外设来保持连接的模拟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系统正常运行更为关键。在所提出的架构中，三个等距的霍尔元件嵌入在一个霍尔传感器将用于检测和测量任何类型的外部EMI欺骗攻击。提出了一种新的算法，利用FPGA和DSP两种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与DSP核之间的通信采用直接存储器存取（DMA）方式来增加带宽。此外，所提出的方法将是低功率的，并且不会妨碍所连接的模拟RF系统的现有数据处理速度和数据速率。该技术不仅检测外部EMI欺骗攻击，而且还包含真实的霍尔传感器内部的攻击，使得攻击不能进一步传播到连接的模拟RF系统。如果成功的话，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。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

MagHop: Magnetic Spectrum Hopping for Securing Voltage and Current Magnetic Sensors

• DOI: 10.1109/host55118.2023.10133158
• 发表时间: 2023-05
• 期刊: 2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)
• 作者: Anomadarshi Barua;M. A. Faruque

A Wolf in Sheep's Clothing: Spreading Deadly Pathogens Under the Disguise of Popular Music

• DOI: 10.1145/3548606.3560643
• 发表时间: 2022-10
• 期刊: Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Anomadarshi Barua;Yonatan Gizachew Achamyeleh;M. A. Faruque

HALC: A Real-time In-sensor Defense against the Magnetic Spoofing Attack on Hall Sensors

• DOI: 10.1145/3545948.3545964
• 发表时间: 2022-10
• 期刊: Proceedings of the 25th International Symposium on Research in Attacks, Intrusions and Defenses
• 作者: Anomadarshi Barua;M. A. Faruque

BayesImposter: Bayesian Estimation Based.bss Imposter Attack on Industrial Control Systems

• DOI: 10.1145/3564625.3564638
• 发表时间: 2022-10
• 期刊: Proceedings of the 38th Annual Computer Security Applications Conference
• 作者: Anomadarshi Barua;Lelin Pan;M. A. Faruque

PreMSat: Preventing Magnetic Saturation Attack on Hall Sensors

• DOI: 10.46586/tches.v2022.i4.438-462
• 发表时间: 2022-08
• 期刊: IACR Trans. Cryptogr. Hardw. Embed. Syst.
• 作者: Anomadarshi Barua;M. A. Faruque