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 paper 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 paper presents a roadmap indicating clearly the actions to be taken to fulfill hardware trust and assurance objectives.
翻译:在硬件信任和保证方面,反向工程往往被视为一种非法行动,一般而言,反向工程的目的是从一种产品,即综合电路(ICs)和印刷电路板(PCBs)中检索与硬件安全有关的情景中的信息,希望了解该装置的功能并确定其组成部分,因此,它可能会在知识产权(IP)的侵害、与安保有关的措施的(在)效力,甚至注射硬件Trojans的新机会方面引起严重问题。具有讽刺意味的是,反向工程可以使IP所有人核查和验证设计,然而,如果不克服限制反向工程进程成功结果的许多障碍,这是无法实现的。本文从两个互补的角度对这些挑战进行了分析:图像处理和机器学习。这两个研究领域构成了提高多氯联苯和ICs反向工程过程的效率和准确性的坚实基础。因此,本文件概要地提出一个路线图,明确表明为实现硬件信任和保证目标而需采取的行动。