Aging Analysis of Low Dropout Regulator for Universal Recycled IC Detection

Chowdhury, Sreeja; Shen, Haoting; Park, Beomsoo; Maghari, Nima; Forte, Domenic

doi:10.1109/isvlsi.2019.00113

Cited by 8 publications

(9 citation statements)

References 10 publications

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“…In Refs. [3,4], accelerated aging on stand-alone LDOs were observed. Both the papers enlisted the degradation of several parameters and the effect of the same on the LDO's PSRR across hours.…”

Section: Experimental Setup and Aging Analysismentioning

confidence: 91%

“…The degradation of electrical parameters like PSRR in Ref. [4] for stand-alone LDOs demonstrates the possibility of degradation over usage/recycling. The successful implementation of recycled detection for stand-alone commercial-off-the-shelf (COTS) LDOs in Ref.…”

Section: Proposed Methodologymentioning

confidence: 99%

“…To observe the effect of accelerated transistor aging on the PSRR and other properties of an LDO, we previously fabricated an LDO in TSMC 65nm process in Ref. [4]. Our experimental results in Fig.…”

Section: Low Dropout (Ldo) Regulatorsmentioning

confidence: 99%

“…[3]. At first, we observed that LDO PSRR is prone to degradation with accelerated transistor aging [4]. The effects of aging degradation on the pass transistor (PT) were depicted from the deviation in current-voltage (IV) characteristics of the PMOS PT and also in the overall PSRR.…”

Section: Introductionmentioning

confidence: 99%

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Recycled SoC Detection Using LDO Degradation

2020

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Counterfeit electronics form a major roadblock towards a safe and successful economy. An increase in globalization has led to a major increase in the total number of counterfeit products all around the world. While several methods have been designed to detect counterfeits, very few of them have been applied to the system-on-chip (SoC). The influx of a variety of components in SoCs and the conglomeration of different types of properties makes it difficult to detect counterfeit SoCs. In this paper, we aim at detecting recycled counterfeit SoCs by evaluating the degradation of power supply rejection ratio (PSRR) of a low drop-out (LDO) regulator, a principal component of the power supply of the SoC. Since the power supply is a universal component in all SoCs, this method can be considered effective for most SoCs. We apply machine learning (ML) algorithms pertaining to the family of Gaussian mixture models to classify SoCs as recycled or new. Supervised and unsupervised ML algorithms show an accuracy of up to 90% and 74% of recycled detection. We also apply stand-alone LDO PSRR degradation to train the ML algorithm and test on PSRR from embedded LDOs in SoCs. This form of semisupervised ML performed well for our previous experiments of recycled detection with stand-alone LDOs but was not able to distinguish recycled SoCs from new SoCs, thus increasing the number of false detection.

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Section: Experimental Setup and Aging Analysismentioning

confidence: 91%

Section: Proposed Methodologymentioning

confidence: 99%

Section: Low Dropout (Ldo) Regulatorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Recycled SoC Detection Using LDO Degradation

2020

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“…Considering the effect of circuit ageing on PSRR, Chowdhury et al [77] proposed using this parameter to estimate the ageing of LDOs, as well as ICs, including such components in their power delivery networks, in order to determine whether a device has been recycled. To characterize the impact of ageing in PSRR, the authors designed their own LDO chips in 65 nm technology.…”

Section: A Power Supply Rejection Ratiomentioning

confidence: 99%

A Review of Techniques for Ageing Detection and Monitoring on Embedded Systems

Leandro¹,

Martino²,

Fey³

et al. 2023

Preprint

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Embedded digital devices, such as Field-Programmable Gate Arrays (FPGAs) and Systems on Chip (SoCs), are increasingly used in dependable or safety-critical systems. These commodity devices are subject to notable hardware ageing, which makes failures likely when used for an extended time. It is of vital importance to understand ageing processes and to detect hardware degradations early. In this survey, we describe the fundamental ageing mechanisms and review the main techniques for detecting ageing in FPGAs, microcontrollers, SoCs, and power supplies. The main goal of this work is to facilitate future research efforts in this field by presenting all main approaches in an organized way.

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