Nano-Resolution Visual Identifiers Enable Secure Monitoring in Next-Generation Cyber-Physical Systems

TL;DR

This paper introduces nano-resolution dendritic metallic patterns as secure, unclonable identifiers for supply chain tracking, combining fractal pattern generation with advanced image authentication to prevent counterfeiting and cloning.

Contribution

It presents a novel nano-scale visual identification system using dendrites, integrating fractal pattern creation, 2D graph-matching, and digital holography for secure supply chain monitoring.

Findings

Dendrites provide high entropy, unclonability, and security against counterfeiting.

A scalable two-step search method improves identification efficiency.

The system effectively detects adversarial attacks on identifiers.

Abstract

Today's supply chains heavily rely on cyber-physical systems such as intelligent transportation, online shopping, and E-commerce. It is advantageous to track goods in real-time by web-based registration and authentication of products after any substantial change or relocation. Despite recent advantages in technology-based tracking systems, most supply chains still rely on plainly printed tags such as barcodes and Quick Response (QR) codes for tracking purposes. Although affordable and efficient, these tags convey no security against counterfeit and cloning attacks, raising privacy concerns. It is a critical matter since a few security breaches in merchandise databases in recent years has caused crucial social and economic impacts such as identity loss, social panic, and loss of trust in the community. This paper considers an end-to-end system using dendrites as nano-resolution visual identifiers to secure supply chains. Dendrites are formed by generating fractal metallic patterns on transparent substrates through an electrochemical process, which can be used as secure identifiers due to their natural randomness, high entropy, and unclonable features. The proposed framework compromises the back-end program for identification and authentication, a web-based application for mobile devices, and a cloud database. We review architectural design, dendrite operational phases (personalization, registration, inspection), a lightweight identification method based on 2D graph-matching, and a deep 3D image authentication method based on Digital Holography (DH). A two-step search is proposed to make the system scalable by limiting the search space to samples with high similarity scores in a lower-dimensional space. We conclude by presenting our solution to make dendrites secure against adversarial attacks.