AEM-PCB Reverser: Circuit Schematic Generation in PCB Reverse Engineering Using Reinforcement Learning Based on Aesthetic Evaluation Metric

PCB reverse engineering plays a crucial role in verifying circuit design, detecting hardware Trojans, and maintaining outdated devices. The reverse generation of PCB schematics, a vital aspect of this engineering, heavily relies on manual design due to the challenge of objectively evaluating schematic quality. This paper introduces a novel aesthetic evaluation metric 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.