Recycled Analog and Mixed Signal Chip Detection at Zero Cost Using LDO Degradation
Sreeja Chowdhury, Fatemeh Ganji, Troy Bryant, Nima Maghari, Domenic J. Forte · 2019
Counterfeit electronics impact the global economy and pose life-threatening risks to critical systems and infrastructure. Analog/mixed-signal (AMS) chips are the most widely reported counterfeit chip type, but existing countermeasures are impractical for detecting them. In this paper, we propose a method to detect recycled AMS counterfeits that exploits degradation of power supply rejection ratio (PSRR) in low drop out (LDO) regulators. Our zero cost approach does not require information about the component's design. Moreover, due to the ubiquity of LDOs, it may apply to active and legacy AMS system on chips (SoCs). To evaluate the feasibility and effectiveness of our method, we use an automated test setup to collect PSRR data from commercial off-the-shelf LDOs before and after aging. Machine learning algorithms ranging from unsupervised to supervised are applied to differentiate between aged (i.e., synthetically recycled) and new LDOs. Silicon results confirm that semi-supervised and supervised algorithms are effective even with LDOs used less than 10 days (for 65nm technology node).