Hong Kong - 4 days ago

A research team from the Department of Electronic Engineering at The Chinese University of Hong Kong (CUHK) has successfully developed chip-scale reconfigurable physical unclonable functions (PUFs), also known as “digital fingerprint” technology, based on carbon nanotubes. This innovation offers high-level security for smart devices, particularly against attacks targeting artificial intelligence (AI) and machine learning systems. It holds promising potential for applications in autonomous vehicles, such as robotics, drones and unmanned aerial vehicles, and the Internet of Things (IoT) systems. The research findings have been published in the well-known international journal Nature Communications.
Turning randomness into a defence against attacks
The rise of edge intelligence – where devices analyse data locally rather than relying on cloud servers – is resulting in increased vulnerability to hacking, physical cloning and reverse engineering. To counter these security risks, hardware-based authentication and trust protocols are required to combat counterfeiting, prevent unauthorised access and secure the communications between edge devices. PUFs, also known as the “fingerprints” of hardware, are  physical objects whose operation cannot be cloned in a physical sense by creating identical hardware. For a given input and conditions (i.e. challenge), PUFs are made possible by exploiting tiny, uncontrollable variations from the hardware fabrication process to generate unique, unclonable responses when challenged, providing a physically defined digital fingerprint output (i.e. response) that serves as a unique identifier.
Traditional PUFs are built on silicon technologies, but they face limitations in entropy, reconfigurability or resilience against modern AI and machine learning-driven attacks. A research team led by Dr Liu Yang, Dr Pei Jingfang and Professor Hu Guohua from the Department of Electronic Engineering at CUHK has developed a new approach using the random distribution of carbon nanotubes in large-scale reconfigurable memory device fabrication. This technique enables both physical unclonability and dynamic reconfigurability, two critical features in enhancing edge device security. Its reconfigurability allows PUFs to generate challenge-response pairs dynamically without recalling the chips, which is especially valuable in resource-constrained edge environments. This scalable, solution-based fabrication approach is also crucial for widespread PUF deployment in edge intelligence.
Innovations from materials science to electronic circuits demonstrate high security to resist attacks and cracking
Carbon nanotubes, a one-dimensional nanomaterial with high carrier concentration, high mobility and tunable electronic properties, lay the foundation for this innovation. Dr Liu Yang said: “By designing and fabricating carbon nanotube memory arrays, the team prototyped PUFs and demonstrated that they could be programmed into over 1013 possible configurations, representing unprecedented reconfigurability for PUFs.” The PUFs achieved ideal randomness, uniqueness and reliability, outperforming prior solutions. Moreover, the reconfigured PUFs also demonstrated great performance in repeated primitive generation operations, outperforming other reports.
By exploiting the idea of physical unclonability, the carbon nanotube PUFs demonstrated exceptional resilience, proving that they provide high security. Dr Pei Jingfang said: “The experimental results showed that even advanced AI and machine learning algorithms could only achieve about 50–60% success rate in attacking the PUFs, essentially no better than random guessing. In addition, brute-force attacks would require an estimated 1016 years for successfully cracking a 108-bit PUF primitive. The demonstrations underscored the robustness of the PUFs in resisting attacks and cracking.”
With this resilience and high security, as a proof of concept, the researchers designed a key-exchange protocol to secure self-driving vehicular communication networks. Embedded in a self-driving vehicular network model in Hong Kong’s Central district, the key-exchange protocol ensured vehicular communication with fast authentication, low computational overhead and minimal latency.
Towards large-scale integration and deployment
Professor Hu Guohua said: “While our carbon nanotube PUF shows these promising results, the lab-to-fab gap needs to be bridged. Future efforts will focus on adapting carbon nanotube PUF fabrication to industrial-scale photolithographic processes, achieving complementary metal-oxide-semiconductor (CMOS) integration for the embedding of analogue front ends and digital logic on a single chip.” In the future, it will be necessary to integrate multi-channel data converters and microprocessors into the system, combining hardware and algorithms to promote their application across various domains.
The full research article can be accessed here:
Nature Communications https://doi.org/10.1038/s41467-025-63739-x

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