The ubiquitous presence of printed circuit boards (PCBs) in modern electronic systems and embedded devices makes their integrity a top security concern. To take advantage of the economies of scale, today's PCB design and manufacturing are often performed by suppliers around the globe, exposing them to many security vulnerabilities along the segmented PCB supply chain. Moreover, the increasing complexity of the PCB designs also leaves ample room for numerous sneaky board-level attacks to be implemented throughout each stage of a PCB's lifetime, threatening many electronic devices. In this paper, we propose PDNPulse, a power delivery network (PDN) based PCB anomaly detection framework that can identify a wide spectrum of board-level malicious modifications. PDNPulse leverages the fact that the PDN's characteristics are inevitably affected by modifications to the PCB, no matter how minuscule. By detecting changes to the PDN impedance profile and using the Frechet distance-based anomaly detection algorithms, PDNPulse can robustly and successfully discern malicious modifications across the system. Using PDNPulse, we conduct extensive experiments on seven commercial-off-the-shelf PCBs, covering different design scales, different threat models, and seven different anomaly types. The results confirm that PDNPulse creates an effective security asymmetry between attack and defense.

翻译：印刷电路板（PCB）在现代电子系统和嵌入式设备中无处不在，其完整性已成为首要安全问题。为利用规模经济优势，当今PCB的设计与制造常由全球供应商完成，这使得PCB在分段式供应链中面临诸多安全漏洞。此外，日益复杂的PCB设计也为各类隐蔽的板级攻击提供了充足空间，此类攻击可能贯穿PCB生命周期的各个阶段，威胁众多电子设备。本文提出PDNPulse——一种基于电源分配网络（PDN）的PCB异常检测框架，能够识别多种板级恶意篡改。PDNPulse利用的原理是：无论篡改多么微小，PDN的特性都会不可避免地受到影响。通过检测PDN阻抗特征的变化，并应用基于弗雷歇距离的异常检测算法，PDNPulse能够稳健且成功地识别系统中的恶意篡改。我们利用PDNPulse在七款商用现货PCB上开展了广泛实验，覆盖不同设计规模、不同威胁模型以及七种不同类型的异常。实验结果证实，PDNPulse在攻击与防御之间构筑了有效的安全非对称性。