학술논문
AEM-PCB Reverser: Circuit Schematic Generation in PCB Reverse Engineering Using Reinforcement Learning Based on Aesthetic Evaluation Metric
Document Type
Periodical
Source
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on. 43(5):1608-1612 May, 2024
Subject
Language
ISSN
0278-0070
1937-4151
1937-4151
Abstract
PCB reverse engineering plays a crucial role in verifying circuit design, detecting hardware Trojans, and maintaining outdated devices. The reverse generation of printed circuit board (PCB) schematics, a vital aspect of this engineering, heavily relies on manual design due to the challenge of objectively evaluating schematic quality. This article introduces a novel acrlong AEM to assess the quality of PCB schematics. Based on this metric, a PCB schematic reverse generation method using reinforcement learning is proposed. Experimental results demonstrate the metric and method’s reliability and effectiveness, as they can automatically generate PCB schematics comparable to those designed by human engineers.