Ni-Doped SnO₂ Gas Sensor Array Enabled High-Randomness PUF for Hardware Security Applications.

Area of Science:

• Materials Science
• Electrical Engineering
• Computer Science

Background:

• Conventional silicon-circuit-based Physical Unclonable Functions (PUFs) in Internet of Things (IoT) systems face challenges with circuit overhead, design complexity, and system integration.
• Growing security demands for IoT sensor nodes necessitate innovative and efficient PUF solutions.

Purpose of the Study:

• To propose and validate a lightweight gas sensor PUF (GS-PUF) design for enhanced security in IoT sensor nodes.
• To utilize intrinsic randomness from gas sensor fabrication and gas-material interactions as entropy sources for PUF response generation.

Main Methods:

• Fabrication of Ni-doped SnO2 nanomaterials using electrostatic spray deposition (ESD).
• Construction of an indirectly heated gas sensor array to improve sensitivity and stability.
• Implementation of a random resistance balancing algorithm based on multi-sensor combinational comparison for generating 128-bit PUF responses.

Main Results:

• Achieved high information entropy (>0.99) and well-balanced output bit distribution (49.88% '1', 50.12% '0').
• Demonstrated excellent inter-device uniqueness (49.8%) and passed all NIST randomness tests with high statistical confidence (min p-value > 0.0368).
• Exhibited long-term PUF response reliability above 96% and offered a lightweight, integrated sensing-security approach for IoT.

Conclusions:

• The proposed GS-PUF effectively reuses intrinsic gas sensor variations for robust security, overcoming limitations of traditional silicon PUFs.
• This method provides a lightweight and integrated solution for securing IoT sensor nodes without additional dedicated PUF circuits.
• The GS-PUF demonstrates superior randomness, uniqueness, and reliability, making it a promising candidate for IoT security applications.