In the context of hardware trust and assurance, reverse engineering has been often considered as an illegal action. Generally speaking, reverse engineering aims to retrieve information from a product, i.e., integrated circuits (ICs) and printed circuit boards (PCBs) in hardware security-related scenarios, in the hope of understanding the functionality of the device and determining its constituent components. Hence, it can raise serious issues concerning Intellectual Property (IP) infringement, the (in)effectiveness of security-related measures, and even new opportunities for injecting hardware Trojans. Ironically, reverse engineering can enable IP owners to verify and validate the design. Nevertheless, this cannot be achieved without overcoming numerous obstacles that limit successful outcomes of the reverse engineering process. This article surveys these challenges from two complementary perspectives: image processing and machine learning. These two fields of study form a firm basis for the enhancement of efficiency and accuracy of reverse engineering processes for both PCBs and ICs. In summary, therefore, this article presents a roadmap indicating clearly the actions to be taken to fulfill hardware trust and assurance objectives.

中文翻译：

---

通过逆向工程获得硬件信任和保证：图像分析和机器学习视角的教程和展望

在硬件信任和保证的背景下，逆向工程通常被认为是一种非法行为。一般来说，逆向工程旨在从产品中检索信息，即硬件安全相关场景中的集成电路（IC）和印刷电路板（PCB），以期了解设备的功能并确定其组成组件。因此，它可能会引发有关知识产权 (IP) 侵权、安全相关措施的（无效）有效性以及注入硬件木马的新机会等严重问题。具有讽刺意味的是，逆向工程可以使 IP 所有者能够验证和验证设计。然而，如果不克服限制逆向工程过程成功结果的众多障碍，就无法实现这一目标。本文从两个互补的角度调查了这些挑战：图像处理和机器学习。这两个研究领域为提高 PCB 和 IC 逆向工程过程的效率和准确性奠定了坚实的基础。因此，总而言之，本文提出了一个路线图，清楚地表明了为实现硬件信任和保证目标而要采取的行动。