Due to the global offshore fabrication of semiconductors, hardware security problems such as counterfeit ICs and Hardware Trojans (HTs) have affected semiconductor device trustworthiness in critical applications. Previous research has proven the encapsulant material difference exists in the counterfeit ICs. What’s more by using a pulsed THz signal, Terahertz Time-Domain Spectroscopy (THz-TDS) is able to detect the effective refractive index difference between authentic and counterfeit IC packaging. This research has also successfully observed the reflective index difference between authentic and counterfeit by measuring the layer thickness and THz-TDS time delay. However, the accuracy of calculating the effective refractive index depends on the accuracy of the layer thickness and the time delay measurements. Consequently, reflective index difference may arise from noise encountered during data collection, which can affect the accuracy and repeatability of counterfeit detection tasks. In this paper, we utilize an unsupervised machine learning model to further demonstrate the capabilities of THz- TDS in counterfeit IC detection. Additionally, the potential of using THz-TDS to generate a unique fingerprint is also discussed.
Hardware security has been a significant challenge in semiconductor devices, leading to serious issues such as denial of service, data leakage etc at both transistor as well as package level. Detecting the usage state of a target semiconductor sample or generating a unique fingerprint can provide critical information about the sample, aiding in the prevention of counterfeiting to avoid hardware security risks. Terahertz Time-Domain Spectroscopy (THz-TDS) stands out as a powerful and non-destructive tool, capable of probing and analyzing the polymer materials. Its sensitivity to molecular-level changes makes THz-TDS suitable for studying the material, structural, and stress properties of IC packaging under real-world conditions. This research begins by reviewing the composition of Electronic Material Compatibility (EMC) materials and their variance under real-world conditions. Furthermore, the application of THz-TDS for polymer material characterization, which incloudes material, structural, and internal stress characterization, is also thoroughly reviewed. By combining these factors, we explore the potential and capability of using THz-TDS to detect real-world loaded samples and the feasibility of generating fingerprints for identifying counterfeit samples, including reused, recycled, or tampered ones.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.