
< The research team. From left: Dr. Geon Gug Yang and Professor Sang Ouk Kim from KAIST. In the circles, from left: Professor Seok Joon Kwon and Ph.D. student Seong-Gyun Im from Sungkyunkwan University. >
Shine a light, and the real can be distinguished from the fake. KAIST researchers have developed a security technology that uses unique “artificial fingerprints” created by the random assembly of nanoparticles. Although extremely difficult to replicate, these fingerprints can be conveniently authenticated using only a smartphone flashlight and a laser pointer, opening up potential applications in anti-counterfeiting and electronic device authentication.
KAIST announced on August 26 that a research team led by Professor Sang Ouk Kim from the Department of Materials Science and Engineering, in collaboration with a team led by Professor Seok Joon Kwon of Sungkyunkwan University, has developed a new foundational security technology based on randomly assembled colloidal nanopatterns—unique microscopic patterns formed by particles too small to be seen with the naked eye. The technology enables authentication using everyday light sources such as smartphone flashlights and laser pointers.

< Figure 1. Schematic illustration of polycrystalline colloidal self-assembly and the PUF authentication method. >
Recent advances in artificial intelligence have made cyberattacks increasingly sophisticated, while future quantum computers may pose a threat to conventional cryptographic systems. As a result, growing attention is being paid to technologies that use the unique physical characteristics of products or devices themselves for security, in addition to software-based encryption.
A physical unclonable function, or PUF, is a security technology that uses minute physical differences naturally generated during the manufacturing process as security information. Just as every person has a unique fingerprint, microscopic particles form a different arrangement each time they assemble. Even when the same materials and process are used, reproducing the exact positions and orientations of the particles is extremely difficult. The researchers used these differences as “artificial fingerprints” for authenticating products and devices.
However, conventional high-security PUFs typically require expensive microscopes, spectroscopic equipment, or imaging systems to read information from their tiny and complex structures, making them difficult to use conveniently in everyday settings.
The research team focused on solving this dilemma between high security and easy authentication. By using the self-assembly of spherical particles hundreds of nanometers in size on a water surface, the team created unique structures composed of many small crystalline domains with different sizes and orientations. These structures are different every time they are made, making them difficult to replicate, while also producing clear optical signals when illuminated.
The research team implemented an authentication method in which the two patterns generated by each product are registered in advance and subsequently compared with those observed from the actual product. In other words, a single “nanofingerprint” is authenticated using two different light sources: a flashlight and a laser. Much like identifying a person using both their face and fingerprint, verifying one nanostructure in two independent ways strengthens security.
When illuminated with ordinary light, such as a smartphone flashlight, the nanostructure produces a unique color and reflection pattern depending on the particle arrangement. When illuminated with a laser pointer, the microscopic particle structure scatters the light in multiple directions, producing a second distinctive optical pattern.
To create a counterfeit, a forger would have to reproduce not only the nanoparticle structure itself, but also the exact color and reflection pattern produced under a flashlight and the optical pattern generated under laser illumination—making replication extremely difficult.
The researchers also successfully transferred the nanostructures onto a variety of surfaces, including flexible plastics, metals, transparent films, and hydrogels—soft, gel-like materials capable of retaining large amounts of water.
The technology could be used to assign a unique “hardware ID” to electronic products and Internet of Things devices for product authentication. It could also serve as an anti-counterfeiting label for luxury goods, artworks, and pharmaceuticals. Because it can be applied to transparent films, it may also be developed into security stickers that do not obscure a product’s design or appearance.

< Figure 2. Demonstration of polycrystalline PUF devices for passport, biometric, and underwater authentication. >
Professor Sang Ouk Kim of KAIST’s Department of Materials Science and Engineering said, “The key achievement of this study is that it combines randomly formed structures that are extremely difficult to replicate with a simple authentication method using readily available tools such as a flashlight or laser pointer.” He added, “We expect the technology to develop into a next-generation security solution that can be readily used in everyday applications, including electronic device authentication and anti-counterfeiting labels.”
Dr. Geon Gug Yang of KAIST’s Department of Materials Science and Engineering and Ph.D. student Seong-Gyun Im of Sungkyunkwan University’s Department of Chemical Engineering contributed equally as co-first authors. Professors Sang Ouk Kim of KAIST and Seok Joon Kwon of Sungkyunkwan University served as co-corresponding authors. The results were published online on July 23 in the international journal Nature Communications.
Paper title: “Dual-space visible light authentication toward high security physical unclonable function”
DOI: https://doi.org/10.1038/s41467-026-75781-4
This research was supported by the Mid-Career Researcher Program and the InnoCORE Program funded by the Ministry of Science and ICT, as well as by the Samsung Research Funding & Incubation Center for Future Technology.
Clues to stress can be hidden in everyday habits such as chatting, searching, and making payments on a smartphone. KAIST researchers have developed a technology that analyzes several routine behaviors repeatedly performed within apps to identify a person’s daily stress state. KAIST (President Choongsik Bae) announced on October 15 that a research team led by Professor Uichin Lee from the Department of AI Computing developed “SHIRBT-MMF,” a technology that automatically ident
2026-10-15KAIST hosted “Physical AI KOREA 2026” at its Daejeon campus on October 13. At the event, KAIST presented physical AI platform technologies that can be applied not only to manufacturing but also to healthcare, defense, logistics, and everyday life, as well as strategies for research, education, and entrepreneurship that can be utilized by a wide range of companies. Humanoid robots are beginning to surpass human records in robotic competitions modeled after Olympic events such as tr
2026-10-12Technologies that reduce noise using thin, lightweight structures, make wireless charging devices lighter, and enable robots to navigate and perform tasks autonomously will be on display at the 2026 KAIST Tech Fair. The event will give companies an opportunity to explore technologies developed in KAIST laboratories and discuss potential applications in their products and manufacturing processes directly with the researchers. KAIST announced on October 12 that it will hold the 2026 KAIST Tech
2026-10-12When new information is continually added and old information is removed, an AI system may fail to find the correct material even when that material exists. KAIST researchers have developed a vector database technology that preserves the search paths leading to the needed information as data changes. This allows AI to find up-to-date information more accurately and quickly. KAIST (President Choongsik Bae) announced on October 5 that a research team led by Professor Min-Soo Kim from the School
2026-10-06For a wearable device to distinguish walking from a brief swing of the arm, it must recognize how a movement changes over time. Korean researchers have developed a technology that stacks semiconductor devices with different response speeds, allowing them to recognize both a change that has just occurred and the changes before it. The technology could be applied to small devices that are worn on or attached to the body to analyze movement and physiological signals. KAIST (President Choongsik B
2026-09-29