Magnetic Tags with Unique Self-Assembly Patterns for Tracking Applications

Abstract Unique tags are often added to items to prevent counterfeiting and tampering. While there are many techniques for generating unique patterns, tags that are inexpensive, scalable, easy to read, and difficult to replicate are particularly useful for tracking applications. In this work, we present a novel tagging concept that utilizes self-assembly methods to create physically unclonable patterns using magnetic particles. By combining a distribution of Nd-Fe-B magnetic particles with a hard polymer inside a strong magnetic field, patterns are generated that are easily read using magneto-optic techniques. Image processing and template matching techniques are then used to determine the likelihood that two different magnetic tags are classified as the same. For optimal selections of particle percent mass, statistical analysis predicts that pattern matching yields at most one false positive for every 1015 true positives. Results further illustrate that variations in particle size and particle percent mass have a strong effect on the predicted pattern uniqueness. Finally, a magnetic field model was then used to help predict broad trends in pattern statistics and particle structures. This paper shows that magnetic self-assembly patterns hold promise as unique embedded tags for a broad range of applications from microelectronics to luxury goods to low-cost off-the-shelf items.