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IEEE World Forum on Internet of Things (WF-IoT)

Quantum PUF and its Applications with Information Theoretic Analysis

Kumar Nilesh, Christian Deppe, Holger Boche

Published Nov 10, 2024• 12 citations
Publisher

Abstract

Physical Unclonable Functions (PUFs) have garnered significant attention for their potential in enhancing the security of IoT devices, offering an alternative to traditional computational-based approaches. Despite their potential, classical PUFs suffer from critical drawbacks, including vulnerability to machine learning attacks and inadequate defense against quantum adversaries. To address these limitations, alternative architectures utilizing quantum mechanical principles, known as Quantum PUFs (QPUFs), have been proposed. This paper presents a comprehensive survey of the diverse range of QPUFs, detailing their architectures and security features. Additionally, it explores the information-theoretic applications of QPUFs in IoT, including secret key generation, secure storage, authentication, and identification. The findings indicate that classical results translate effectively to the quantum domain in most cases, with QPUFs exhibiting larger capacity regions compared to their classical counterparts.

DOI
10.1109/wf-iot62078.2024.10811185

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Physical Unclonable Functions (PUFs) have garnered significant attention for their potential in enhancing the security of IoT devices, offering an alternative to traditional computational-based approaches. Despite their potential, classical PUFs suffer from critical drawbacks, including vulnerability to machine learning attacks and inadequate defense against quantum adversaries. To address these limitations, alternative architectures utilizing quantum mechanical principles, known as Quantum PUFs (QPUFs), have been proposed. This paper presents a comprehensive survey of the diverse range of QPUFs, detailing their architectures and security features. Additionally, it explores the information-theoretic applications of QPUFs in IoT, including secret key generation, secure storage, authentication, and identification. The findings indicate that classical results translate effectively to the quantum domain in most cases, with QPUFs exhibiting larger capacity regions compared to their classical counterparts.
Physical Unclonable Functions (PUFs) have emerged as a powerful cryptographic tool for various applications due to their inherent physical uniqueness and unclonability. However, the advent of quantum computers has posed significant threats to classical PUFs. In response, Quantum PUFs (QPUFs), which exploit the principles of quantum mechanics, have been introduced as a robust alternative. This paper analyzes two key applications of QPUFs utilizing their distinctive output: secure storage and identification, from an information theoretic perspective. We establish achievability under different constraints and derive the secure storage capacity and a doubly exponential identification rate, even in the presence of an active adversary attempting to deceive the system by exploiting publicly stored data. We further demonstrate that within the quantum domain, we achieve higher rates compared to classical counterparts.
Quantum Physically Unclonable Functions (QPUFs) are emerging hardware primitives that harness inherent quantum principle to produce device-specific challenge–response behavior. By embedding quantum-mechanical "fingerprints" into devices, QPUFs can derive unique cryptographic keys and identities, yielding robust hardware roots of trust. This paper systematically reviews QPUF principles, architectures, and security properties, and explores their integration into next-generation networking paradigms with industrial demonstrations. We detail how QPUFs can enable secure device authentication, key generation across quantum communication links, 6G wireless, IoT/edge deployments emphasizing practical implementation strategies and system integration in future networks along with technical challenges. Through this comprehensive analysis, we highlight the transformative potential of QPUFs in delivering hardware-rooted, information-theoretic security for interconnected networks, and outline directions for further research.
Physically Unclonable Functions (PUFs) have emerged as critical primitives for secure authentication and key generation. However, classical PUFs are increasingly vulnerable to machine learning and quantum-enabled attacks. Quantum PUFs, leveraging the principles of quantum mechanics, provide a promising alternative offering information-theoretic security. In this work, we present an information-theoretic framework for two key applications of QPUFs: secret key generation and secure data storage. We rigorously characterize the trade-offs between achievable key and storage rates under various privacy leakage constraints—unconditional, conditional, and zero-leakage—extending classical results into the quantum domain. We derive single-letter capacity expressions based on Holevo information and analyze the impact of shared private randomness on achieving zero privacy leakage. Our results establish fundamental performance limits for QPUF-based security systems and lay the foundation for cryptographic key generation and storage protocols in future quantum-resilient communication infrastructures.
Quantum Physical Unclonable Functions (QPUFs) offer a physically grounded approach to secure authentication, extending the capabilities of classical PUFs. This review covers their theoretical foundations and key implementation challenges—such as quantum memories and Haar‐randomness—, and distinguishes QPUFs from Quantum Readout PUFs (QR‐PUFs), more experimentally accessible yet less robust against quantum‐capable adversaries. A co‐citation‐based selection method is employed to trace the evolution of QPUF architectures, from early QR‐PUFs to more recent Hybrid PUFs (HPUFs). This method further supports a discussion on the role of information‐theoretic analysis in mitigating inconsistencies in QPUF responses, underscoring the deep connection between secret‐key generation and authentication. Despite notable advances, achieving practical and robust QPUF‐based authentication remains an open challenge.
The Internet of Things (IoT) has ushered in significant advancements in networked technologies, yet it simultaneously raises concerns about the security and privacy of connected devices. Traditional authentication methods based on cryptographic protocols are increasingly vulnerable to attacks as the number of devices grows and attackers develop more sophisticated strategies. In this paper, we propose a novel quantum-based authentication method using Quantum Physical Unclonable Functions (QPUFs) to address the security challenges in IoT devices. Quantum PUFs exploit the inherent quantum properties of devices to generate unique, unclonable responses to challenges, providing a high level of security and resilience against attacks such as cloning, spoofing, and interception. We present the architecture of the proposed quantum authentication system, discuss the challenge-response protocol, and evaluate the system’s performance. Experimental results show that this approach offers strong security guarantees with minimal computational overhead. We Evaluate the Security, Scalability of our approach in simulated adverse IoT environment.
An information-theoretic analysis of secure authentication based on Quantum Physically Unclonable Functions (QPUF) is presented in this paper. The proposed model employs a secret key generated through QPUF to authenticate pre-enrolled user and device identities while maintaining secrecy and limiting privacy leakage. We analyze the system's robustness against an active adversary who exploits publicly available data to impersonate legitimate users with fraudulent inputs. Our analysis focuses on characterizing the capacity region of the adversary's false acceptance exponent alongside the privacy leakage under reliability conditions. We further demonstrate that the achievable capacity region in the quantum domain surpasses that of classical systems. Additionally, we derive an optimal trade-off among the false acceptance exponent, public storage rate, and privacy leakage rate, offering key insights into the system's asymptotic performance.