The conventional use of ID verification tags has faced a significant loophole: peeling them off and affixing them to counterfeit products renders them ineffective. In response, MIT scientists have devised a revolutionary ID tag system that leverages the adhesive itself as a unique fingerprint, ensuring that the barcode becomes scrambled if an attempt is made to peel it off.

The underlying principle of these ID tags aligns with radio frequency identification tags (RFIDs), commonly employed for inventory tracking and authenticity verification. Each tag possesses a distinct identifying code, detectable through a scanner to validate the authenticity of the item. However, the prior flaw lay in merely verifying the tag’s authenticity rather than the item to which it was attached. The MIT team’s solution involved developing a tag that obliterates its barcode upon removal.

The key innovation lies in embedding the ID not within the tag but in the adhesive binding it to the item. Microscopic metal particles are infused into the glue, and post-application, the tag is scanned using high-frequency terahertz waves. These waves interact with the metal particles, capturing their unique arrangement, effectively creating a fingerprint stored in the cloud. When someone attempts to peel off the tag and reapply it to another item, the specific arrangement of metal particles in the glue is disrupted, resulting in an incorrect ID upon subsequent scanning.

Ruonan Han, one of the study’s authors, explained, “These metal particles are essentially like mirrors for terahertz waves. If you peel the chip off and reattach it, you destroy that pattern.” The ID tag is compact, measuring a mere 4 mm² (0.006 in²), making it versatile for attachment to various items. Moreover, it is cost-effective for large-scale production, with a machine learning model achieving over 99% accuracy in detecting the unique patterns.

While the current system works effectively with a sensor up to 4 cm (1.6 in) away and within a 10-degree angle, limitations exist for applications like recognizing vehicles passing through toll booths. The researchers are committed to addressing these challenges in future iterations of the technology, ensuring broader adaptability and enhanced security in various scenarios.

By Impact Lab