Outsourcing integrated circuit (IC) design, fabrication, and test facilities has become common because it reduces costs and time-to-market. Such outsourcing allows external entities full access to all the design details, e.g. GDSII layout and test vectors (test inputs and test responses). As a result, the foundry is left vulnerable to hardware Trojan (HT) insertion from the design house. HT is any malicious modification to the circuit which occurs at any phase of design, integration, or fabrication [1]. Since ICs are prevalent in modern electronic devices, HTs can compromise the security and trustworthiness of critical infrastructures, such as those within the civilian, military, and medical domains [2], [3].

IC camouflaging has been proposed as a promising countermeasure against malicious reverse engineering. Camouflaged gates contain multiple functional device structures, but appear as one single layout under microscope imaging, thereby hiding the real circuit functionality from adversaries. The recent covert gate camouflaging design comes with a significantly reduced overhead cost, allowing numerous camouflaged gates in circuits and thus being resilient against various invasive and semi-invasive attacks. Dummy inputs are used in the design, but SEM imaging analysis was only performed on simplified dummy contact structures in prior work. Whether the e-beam during SEM imaging will charge differently on different contacts and further reveal the different structures or not requires extended research. In this study, we fabricated real and dummy contacts in various structures and performed a systematic SEM imaging analysis to investigate the possible charging and the consequent passive voltage contrast on contacts. In addition, machine-learning based pattern recognition was also employed to examine the possibility of differentiating real and dummy contacts. Based on our experimental results, we found that the difference between real and dummy contacts is insignificant in SEM imaging, which effectively prevents adversarial SEM-based reverse engineering. Index Terms—Reverse Engineering, IC Camouflaging, Scanning Electron Microscopy, Machine Learning, Countermeasure.