JOURNAL ARTICLE

A Measurement System for Capacitive PUF-Based Security Enclosures

Johannes ObermaierMatthias HillerVincent ImmlerGeorg Sigl

Year: 2018 Journal:   2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC) Pages: 1-6

Abstract

Battery-backed security enclosures that are permanently monitored for penetration and tampering are common solutions for providing physical integrity to multi-chip embedded systems. This paper presents a well-tailored measurement system for a batteryless PUF-based capacitive enclosure. The key is derived from the PUF and encrypts the underlying system. We present a system concept for combined enclosure integrity verification and PUF evaluation. The system performs differential capacitive measurements inside the enclosure by applying stimulus signals with a 180 ° phase shift that isolate the local variation in the femtofarad range. The analog circuitry and corresponding digital signal processing chain perform precise PUF digitization, using a microcontroller-based digital lock-in amplifier. The system's measurement range is approximately ± 73 fF, the conversion time per PUF node is less than 0.6 ms, and the raw data shows a measurement noise of 0.3 fF. This is the base for a high-entropy key generation while enabling a short system startup time. The system is scalable to the enclosure size and has been experimentally verified to extract information from 128 PUF nodes, using a system prototype. The results show that our concept forms a cornerstone of a novel batteryless PUF-based security enclosure.

Keywords:
Capacitive sensing Microcontroller Computer science System of measurement Enclosure Embedded system Computer hardware Electronic engineering Electrical engineering Engineering

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16
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0.91
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Citation History

Topics

Physical Unclonable Functions (PUFs) and Hardware Security
Physical Sciences →  Computer Science →  Hardware and Architecture
Integrated Circuits and Semiconductor Failure Analysis
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Neuroscience and Neural Engineering
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
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