Researchers develop a device that converts electrical signals generated by light–matter interactions into true random numbers to authenticate images
SEOUL, South Korea, July 13, 2026 /PRNewswire/ — Developing secure hardware capable of generating truly random numbers is becoming increasingly important as artificial intelligence-generated forgeries and cyber threats grow more sophisticated. Now, researchers have developed a light-driven true random number generator and demonstrated how these numbers can be embedded into images as hidden security signatures to detect tampering. The device could be integrated into image sensors, enabling hardware-based detection of image modifications.
While security systems based on pseudo-random number generators (PRNGs) have been developed to secure information usage, they produce sequences that are not truly random and suffer from inherent vulnerabilities and security breaches. To overcome these limitations, true random number generator (TRNG) that exploit diverse sources of physical entropy has emerged as an alternative technology.
Now, a team of researchers led by Associate Professor Hocheon Yoo from the Department of Electronic Engineering, Hanyang University, Republic of Korea, have developed a photospike-based TRNG (PS-TRNG) that harnesses the unpredictable trapping and release of electrical charges inside semiconductor nanostructures when illuminated with pulses of light. This study was made available online on January 29, 2026, and was published in Volume 38, Issue 33 of the journal in Advanced Materials on June 12, 2026.
The PS-TRNG device consists of copper vanadate nanostructures and a layer of tin dioxide quantum dots placed between a substrate and a transparent conducting polymer electrode. When exposed to pulsed red light, electrons are generated in the substrate and move toward the transparent top electrode. Some of these charges become trapped at randomly distributed defect sites within the quantum-dot layer. When the light is switched off, the trapped electrons are released, producing a reverse current. As the trapping and release occur unpredictably, each pulse produces a slightly different electrical signal. These electrical signals were then digitized into three logic states (0, 1, and 2) using predefined current thresholds, producing ternary true random numbers in real time. The generated ternary random numbers showed near-ideal statistical balance, passed all 15 tests in the National Institute of Standards and Technology randomness test suite, and remained stable over more than two million operating cycles and 460 days of testing.
“Our study could help move image security from software-based post-processing to hardware-level protection at the moment of image acquisition. If light-induced entropy sources are integrated directly into cameras or image sensors, every captured image or video frame could carry a physically generated security fingerprint from the device itself,” says Prof. Yoo.
The researchers demonstrated a practical application by embedding the random numbers as a hidden security signature within digital images without affecting their visible quality. Any image modification changes this signature, enabling pixel-level detection of AI-generated forgeries. Such a system could allow image authentication and deepfake detection in areas where a photo must be trusted, such as news media, legal and forensic evidence, identity documents, and medical images.
“This points toward a world where the authenticity of visual information is guaranteed at the hardware level when an image is created, rather than being judged after the fact, which would make digital images far harder to forge and easier to trust,” concludes Prof. Yoo.
Reference
Title of original paper: Light-Induced Entropy for Secure Vision
Journal: Advanced Materials
DOI: https://doi.org/10.1002/adma.202516947
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