An in-pixel gain amplifier based event-driven physical unclonable function for CMOS dynamic vision sensors

• Main Authors: Wang, Biyin, Zhao, Xiaojin, Zheng, Yue, Chang, Chip-Hong
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Voltage Control; Amplifiers
• Online Access: https://hdl.handle.net/10356/137092
• Institution: Nanyang Technological University

In this paper, a novel in-pixel event-driven physical unclonable function (PUF) is presented for the rapidly developed CMOS dynamic vision sensor (DVS). Different from traditional widely reported PUF implementations with additional dedicated silicon area, power consumption and peripheral circuitries, the proposed implementation extracts PUF based on the original gain amplifier existing in the mainstream DVS pixel, which is necessary to amplify the front-end logarithmic photoreceptor’s relatively weak output signal, according to the ratio of the in- pixel capacitor pair. With any ON/OFF event generated and the corresponding DVS pixel fired asynchronously, the DVS pixel’s own gain amplifier will be reset in order to capture the next possible event. Due to the inevitable variation of the semiconductor fabrication process, the reset voltages of different DVS pixels’ gain amplifiers are slightly different. A bidirectional counter based analog-to-digital converter is customized to digitize the successively fired pixel pair with the sign bit representing the PUF bit (i.e. the reset voltages’ difference). Moreover, the proposed implementation is validated using a standard 0.18μm CMOS process in Cadence. According to the extensive post-layout simulation results, the uniqueness is calculated to be 49.97%. With the operating temperature varying from −40◦C to 120◦C and supply voltage varying from 1.7V to 2.1V, the worst-case reliability is reported to be 96.48% and 97.27%, respectively. Meanwhile, its superior randomness is also verified using the NIST test suite.