Abstract: Embodiments of the present disclosure provide methods, systems, apparatus, and computer program products are for detecting whether a suspect component such as an integrated circuit (IC) or a system-on-chip (SoC) is recycled. Specifically, various embodiments involve processing power supply rejection ratio (PSRR) data obtained from a low drop-out regulator (LDO) used for the suspect component using a recycle detection machine learning model to generate a recycle prediction. In particular embodiments, the recycle detection machine learning model is developed based at least in part on degradation of PSRRs of LDOs. Accordingly, a determination is made as to whether the suspect component is recycled based on the recycle prediction. If so, then an indication that the suspect component is recycled is provided.

Abstract: A method and system are directed to designing a low-dropout regulator (LDO) circuit and using the LDO circuit to detect recycled counterfeit integrated circuits. The LDO circuit includes, in part, a reference path circuit and a stressed path circuit. Each of the reference path circuit and the stressed path circuit is coupled to a control signal that can enable the corresponding path circuit for the LDO. LDO parameters can then be measured while the reference path circuit and the stressed path circuit is enabled respectively. The difference between the LDO parameters measured while the reference path circuit is enabled and while the stressed path circuit is enabled is used to determine if an integrated circuit comprising the LDO circuit is a recycled counterfeit.

Abstract: Embodiments of the present disclosure provide methods, systems, apparatus, and computer program products are for detecting whether a suspect component such as an integrated circuit (IC) or a system-on-chip (SoC) is recycled. Specifically, various embodiments involve processing power supply rejection ratio (PSRR) data obtained from a low drop-out regulator (LDO) used for the suspect component using a recycle detection machine learning model to generate a recycle prediction. In particular embodiments, the recycle detection machine learning model is developed based at least in part on degradation of PSRRs of LDOs. Accordingly, a determination is made as to whether the suspect component is recycled based on the recycle prediction. If so, then an indication that the suspect component is recycled is provided.