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SPAD PUFs: Reconfigurable Physically Unclonable Functions Using Single-Photon Avalanche Diodes
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We present a study on physically unclonable functions (PUFs) derived from the dark signal non-uniformity (DSNU) of a perimeter-gated single-photon avalanche diode (pg-SPAD) CMOS imager. We introduce a method for generating unique and chip-specific signatures by leveraging challenge-response pairs (CRPs) with pixel addresses serving as challenges and pixel dark count values as responses. Furthermore, we demonstrate how perimeter gating can be utilized to reconfigure the CRP space of these PUFs, enhancing their security and versatility. To assess PUF quality, we performed a comprehensive characterization across multiple chips and over a wide temperature range (−35
o
C to 70
o
C). We evaluated PUF metrics like uniqueness, reliability, uniformity, and bit aliasing. Our results indicate that under optimal conditions, the average normalized Hamming distance (nHD) between responses to different challenges approaches the ideal value of 0.5, while the nHD for identical challenges converges toward zero. Finally, we show that column fixed pattern noise enhances PUF reliability.
Title: SPAD PUFs: Reconfigurable Physically Unclonable Functions Using Single-Photon Avalanche Diodes
Description:
We present a study on physically unclonable functions (PUFs) derived from the dark signal non-uniformity (DSNU) of a perimeter-gated single-photon avalanche diode (pg-SPAD) CMOS imager.
We introduce a method for generating unique and chip-specific signatures by leveraging challenge-response pairs (CRPs) with pixel addresses serving as challenges and pixel dark count values as responses.
Furthermore, we demonstrate how perimeter gating can be utilized to reconfigure the CRP space of these PUFs, enhancing their security and versatility.
To assess PUF quality, we performed a comprehensive characterization across multiple chips and over a wide temperature range (−35
o
C to 70
o
C).
We evaluated PUF metrics like uniqueness, reliability, uniformity, and bit aliasing.
Our results indicate that under optimal conditions, the average normalized Hamming distance (nHD) between responses to different challenges approaches the ideal value of 0.
5, while the nHD for identical challenges converges toward zero.
Finally, we show that column fixed pattern noise enhances PUF reliability.
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