Core Concepts
Implementation of large-scale quantum neural reservoirs on-chip enables secure authentication with high reliability and unique key generation.
Abstract
The content discusses the implementation of a quantum-activated neural reservoir on a chip for hardware security models. It covers the fabrication process, characterization using AFM and HRTEM, key generation, validation, and security analysis. The proposed architecture for user authentication is detailed along with performance analysis and resilience against attacks.
Fabrication Process:
- Silicon wafer oxidation and GST film deposition.
- Metal electrode patterning using sputtering.
- Chip integration into a QNR module.
AFM Measurement Results:
- Spatial resistance-voltage maps.
- Resistance-voltage curves at different bias levels.
- Topography images under varying applied voltages.
HRTEM Characterization:
- Evolution of GST film properties at increasing temperatures.
- Nucleation of quantum-sized crystals in the material.
Data-driven Model:
- Schematic diagram of QNR chip setup.
- Nanoscale circuit representation.
- Simulation results of nanocircuit behavior.
Key Generation & Performance Analysis:
- OTK generation process using SND decoder.
- Experimental results of current orbits for different challenges.
- Comparison of bit density per feature size area metrics.
Key Validation & Resilience Analysis:
- Implementation details of VA for key validation.
- Illustration of phase-space stretching in recurrent transformation.
- Inference attack diagram and mutual information analysis between correct and predicted OTKs.
Stats
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Quotes
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