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Photonic physical unclonable functions for co-integration of security and computing functionalities

Fabio Pavanello, Niklas Pirnay, Agraj Yadav, Julien Poëtte, Federico Marchesin, Matéj Hejda, Tzamn Melendez Carmona, Alessandro Savino, Stefano Di Carlo, Thomas Van Vaerenbergh, Peter Bienstman, Jean‐Pierre Seifert

Published Jan 1, 2026• 0 citations
Publisher

Abstract

We propose a novel approach to build photonic physical unclonable functions (PPUFs) by leveraging Mach-Zehnder interferometer (MZI)-based computing mesh architectures. Statistical properties and robustness to machine-learning attacks show promising results for strong PPUFs.
DOI
10.1364/cleo_at.2026.jtu.79

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Physical Unclonable Functions (PUFs) are hardware security primitives whose inherent physical complexity can be exploited for secure authentication and cryptographic key generation. Silicon photonic devices, owing to their suitability for quantum and artificial intelligence applications alongside standard CMOS fabrication processes, constitute a highly promising substrate for integrated multifunctional PUFs. Despite the advanced security guarantees offered by quantum cryptographic protocols and the central role of silicon photonics in quantum technologies, quantum readout strategies based on single-photon states for photonic PUFs remain largely unexplored. In this work, we experimentally demonstrate a silicon nitride (SiN) programmable photonic Mach Zehnder interferometer mesh that implements a unitary transformation and operates as a PUF, whose secret physical signature arises from uncontrollable waveguide variations during fabrication. Using experimentally derived parameters from the SiN integrated mesh, we further introduce and numerically evaluate a quantum readout protocol that combines single-photon states with PUFs. Maximally mixed quantum states are employed to conceal the underlying unitary transformation from passive eavesdropping. Security against adversaries possessing devices fabricated under similar conditions is assessed, with authentication performance quantified through Monte Carlo analysis of the false acceptance and false rejection rates as a function of the number of detected events and corrected errors. The results indicate exceptional performance with equal error rates as low as 10 to the minus 14, highlighting the potential of quantum secure PUFs for high security authentication applications.
Physically unclonable functions (PUFs) have emerged as a promising hardware security primitive, and recent years have seen growing interest in realizing PUFs on photonic integrated circuits (PICs). We classify existing PIC-based PUFs into electrically configured and optically encoded designs. Notably, security properties remain insufficiently analyzed, with mathematical unclonability often assumed without supporting argument. To illustrate this issue, we introduce a modeling attack against the subclass of optically encoded PUFs that operate in a linear optical regime. We show that, for a representative simulated PUF construction, observing as few as 200 challenge-response pairs allows learning the challenge-response mapping. Under canonical modeling assumptions, linear optically encoded PUFs are therefore mathematically clonable, calling for a careful assessment of their suitability for authentication protocols that rely on mathematical unclonability.
In this work, the novel usage of a physically unclonable function composed of a network of Mach-Zehnder interferometers for authentication tasks is described. The physically unclonable function hardware is completely reconfigurable, allowing for a large number of seemingly independent devices to be utilized, thus imitating a large array of single-response physically unclonable functions. It is proposed that any reconfigurable array of Mach-Zehnder interferometers can be used as an authentication mechanism, not only for physical objects, but for information transmitted both classically and quantumly. The proposed use-case for a fully-optical physically unclonable function, designed with reconfigurable hardware, is to authenticate messages between a trusted and possibly untrusted party; verifying that the messages received are generated by the holder of the authentic device.
The hallmark of the information age is the ease with which information is stored, accessed, and shared throughout the globe. This is enabled, in large part, by the simplicity of duplicating digital information without error. Unfortunately, an ever-growing consequence is the global threat to security and privacy enabled by our digital reliance. Specifically, modern secure communications and authentication suffer from formidable threats arising from the potential for copying of secret keys stored in digital media. With relatively little transfer of information, an attacker can impersonate a legitimate user, publish malicious software that is automatically accepted as safe by millions of computers, or eavesdrop on countless digital exchanges. To address this vulnerability, a new class of cryptographic devices known as physical unclonable functions (PUFs) are being developed. PUFs are modern realizations of an ancient concept, the physical key, and offer an attractive alternative for digital key storage. A user derives a digital key from the PUF’s physical behavior, which is sensitive to physical idiosyncrasies that are beyond fabrication tolerances. Thus, unlike conventional physical keys, a PUF cannot be duplicated and only the holder can extract the digital key. However, emerging machine learning (ML) methods are remarkably adept at learning behavior via training, and if such algorithms can learn to emulate a PUF, then the security is compromised. Unfortunately, such attacks are highly successful against conventional electronic PUFs. Here, we investigate ML attacks against a nonlinear silicon photonic PUF, a novel design that leverages nonlinear optical interactions in chaotic silicon microcavities. First, we investigate these devices’ resistance to cloning during fabrication and demonstrate their use as a source of large volumes of cryptographic key material. Next, we demonstrate that silicon photonic PUFs exhibit resistance to state-of-the-art ML attacks due to their nonlinearity and finally validate this resistance in an encryption scenario.
In this work, the novel usage of a physically unclonable function composed of a network of Mach-Zehnder interferometers for authentication tasks is described. The physically unclonable function hardware is completely reconfigurable, allowing for a large number of seemingly independent devices to be utilized, thus imitating a large array of single-response physically unclonable functions. It is proposed that any reconfigurable array of Mach-Zehnder interferometers can be used as an authentication mechanism, not only for physical objects, but for information transmitted both classically and quantumly. The proposed use-case for a fully-optical physically unclonable function, designed with reconfigurable hardware, is to authenticate messages between a trusted and possibly untrusted party; verifying that the messages received are generated by the holder of the authentic device.