Pseudo-Unique Fingerprint for Mass Production Components
Project ID:
P9_24
Principal Investigator:
Dr. Mehdi Anwar
Email:
Co-Principal Investigator(s):
N/A
Topic Areas:
Tamper Resistance/Anti-tamper
Abstract
GDI (Grow-Disperse-Inspect): A Novel Circuit Authentication Tag.
IoT infrastructures and intelligent decision making currently utilizing over 17 billion globally connected IoT devices and that number is expected to double by 2030, will impact all aspects of connected systems, with application platforms ranging from manufacturing and the economy, transportation, education and training, sustainable agriculture and energy, communications and social interactions, just to name a few. The rather inexpensive IoTs along with the exploding number of devices required to satisfy demand will result in opportunities for exploitation and technologies must be developed to ensure integrity of authentic components and their provenance. The proposed research introduces a unique Physically Unclonable Function (PUF) with a unique finger print that is statistically impossible to replicate, as a possible anti-tampering tool for the identification of IoT components. The proposed process being rather simple to implement, fast and integrable to production systems makes it ideal for mass-produced components