Secure Physical Unclonable Functions Research Articles

Traceable Optical Physical Unclonable Functions Based on Germanium Vacancy in Diamonds.

Physical unclonable functions (PUFs) have emerged as an unprecedented solution for modern information security and anticounterfeiting by virtue of their inherent unclonable nature derived from distinctive, randomly generated physical patterns that defy replication. However, the creation of traceable optical PUF tags remains a formidable challenge. Here, we demonstrate a traceable PUF system whose unclonability arises from the random distribution of diamonds and the random intensity of the narrow emission from germanium vacancies (GeV) within the diamonds. Tamper-resistant PUF labels can be manufactured on diverse and intricate structural surfaces by blending diamond particles into polydimethylsiloxane (PDMS) and strategically depositing them onto the surface of objects. The resulting PUF codes exhibit essentially perfect uniformity, uniqueness, reproducibility, and substantial encoding capacity, making them applicable as a private key to fulfill the customization demands of circulating commodities. Through integration of a digitized "challenge-response" protocol, a traceable and highly secure PUF system can be established, which is seamlessly compatible with contemporary digital information technology. Thus, the GeV-PUF system holds significant promise for applications in data security and blockchain anticounterfeiting, providing robust and adaptive solutions to address the dynamic demands of these domains.

Quantum Lock: A Provable Quantum Communication Advantage

Physical unclonable functions(PUFs) provide a unique fingerprint to a physical entity by exploiting the inherent physical randomness. Gao et al. discussed the vulnerability of most current-day PUFs to sophisticated machine learning-based attacks. We address this problem by integrating classical PUFs and existing quantum communication technology. Specifically, this paper proposes a generic design of provably secure PUFs, called hybrid locked PUFs(HLPUFs), providing a practical solution for securing classical PUFs. An HLPUF uses a classical PUF(CPUF), and encodes the output into non-orthogonal quantum states to hide the outcomes of the underlying CPUF from any adversary. Here we introduce a quantum lock to protect the HLPUFs from any general adversaries. The indistinguishability property of the non-orthogonal quantum states, together with the quantum lockdown technique prevents the adversary from accessing the outcome of the CPUFs. Moreover, we show that by exploiting non-classical properties of quantum states, the HLPUF allows the server to reuse the challenge-response pairs for further client authentication. This result provides an efficient solution for running PUF-based client authentication for an extended period while maintaining a small-sized challenge-response pairs database on the server side. Later, we support our theoretical contributions by instantiating the HLPUFs design using accessible real-world CPUFs. We use the optimal classical machine-learning attacks to forge both the CPUFs and HLPUFs, and we certify the security gap in our numerical simulation for construction which is ready for implementation.

Highly Reliable and Secure PUF Using Resistive Memory Integrated Into a 28 nm CMOS Process

Owing to the increased demand for secure communication channels and authentication steps, physical unclonable functions (PUFs) are increasingly important for hardware security. In this article, we report a novel PUF architecture and generation scheme that utilizes the inherent program-time variation of resistive random access memory (ReRAM) cells as an entropy source. ReRAM cells are integrated into a standard 28 nm CMOS manufacturing process, and also show robust non-volatile memory operation. We generated a PUF data set larger than 10 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\text{8}}$</tex-math> </inline-formula> bits and verified its randomness using a standard NIST test suite. Further verifications such as inter-and intra-hamming distance, 150 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\circ}$</tex-math> </inline-formula> C data retention of PUF bits, and spatial co-relation tests confirm the high reliability of the generated PUF keys.

A Subspace Pre-Learning Strategy to Break the Interpose PUF

Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained IoT devices. A critical aspect of PUF security research is to identify all potential security risks. This information about vulnerabilities is beneficial for both PUF developers and PUF-using application developers in terms of designing new PUFs to mitigate existing risks and avoid vulnerable PUFs. Recently, a PUF structure called Interpose PUF (IPUF) was proposed, which claims to be resistant to reliability attacks and machine learning modeling attacks. Related studies on this secure PUF design have demonstrated that some IPUFs can still be broken, but large IPUFs may remain secure against all known modeling attacks. In addition, all these studies either focus on plain challenge–response pair attacks or require prior knowledge of IPUF architecture implementation. However, depending on the claim of attack resistance to reliability attacks, we can employ a different attack approach to break IPUFs. In this paper, we describe a subspace pre-learning-based attack method that can rapidly and accurately break the IPUFs that were treated as secure in the earlier study, revealing a vulnerability in IPUFs if the open interface conforms to the way challenge–response data are accessed by the subspace pre-learning-based attack method.

A Lightweight Hardware Secure and Reliable Framework using Secure and Provable PUF for IoT Devices against the Machine Learning Attack

IoT (Internet of Things) has been expanding into various business activities and people’s lives; however, IoT devices face security challenges. Further, the establishment of reliable security for IoT constrained devices is considered to be ongoing research due to several factors such as device cost, implementation area, power consumption, and so on. In addition to these factors, hardware security also poses major challenges like above mentioned; further Physical Unclonable Functions (PUFs) offer a promising solution for the authentication of IoT devices as they provide unique fingerprints for the underlying devices through their challenge-response pairs. However, PUFs are vulnerable to modelling attacks; in this research work, a lightweight hardware security framework is designed that provides the security for light edge devices. The proposed hardware security framework introduces the three-step optimized approach to offer a secure and reliable solution for IoT device authentication. The first step deals with the designing of SP-PUF, the second step deals with introducing obfuscation technique into the same, and the third step deals with introducing the authentication mechanism. A machine learning attack is designed to evaluate the model and the proposed model is evaluated considering the different stages. This research work is evaluated in two parts; the first part of the evaluation is carried out for the security mechanism through machine learning algorithm attack i.e., logistic regression, Neural Network, and SVM; further evaluation is carried out considering the PUF evaluation parameter as uniqueness and reliability. At last, comparative analysis suggest that proposed hardware security framework is safe against the machine learning attacks and achieves high reliability and optimal uniqueness.

Fabrication and Characterization of 2-Bit per Capacitor as Functional Structures for Physical Unclonable Function Circuits

Currently, security issues for semiconductor chips are counterfeiting and night shift problems. These factors might lead to insecure supply chains in the automotive industry. This can be avoided by using coating Physical Unclonable Functions (PUFs). The coating can be applied to every semiconductor chip in order to create a unique fingerprint. In this work, a 2-bit key per capacitor for Physical Unclonable Functions is presented for the first time. For this reason, 49 chips on a wafer with 195 metal oxide semiconductor (MOS) capacitors were fabricated. A large and random fluctuation of the capacitances was achieved by using a self-developed layer, which consisted of aluminum particles and spin-on glass. Due to the random variation in size and change in distribution of the particles, the fluctuation of capacitance varied from chip to chip and from wafer to wafer. The achieved large range in capacitance was used to create a 390-bit string out of 195 capacitors. Although the length of the bit string was doubled, the area of the structure remained constant. This led to a more secure PUF with a low error rate of 0.21% and an inter-chip Hamming distance (HD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">inter</sub> ) of 49%.

Memristive crypto primitive for building highly secure physical unclonable functions.

Physical unclonable functions (PUFs) exploit the intrinsic complexity and irreproducibility of physical systems to generate secret information. The advantage is that PUFs have the potential to provide fundamentally higher security than traditional cryptographic methods by preventing the cloning of devices and the extraction of secret keys. Most PUF designs focus on exploiting process variations in Complementary Metal Oxide Semiconductor (CMOS) technology. In recent years, progress in nanoelectronic devices such as memristors has demonstrated the prevalence of process variations in scaling electronics down to the nano region. In this paper, we exploit the extremely large information density available in nanocrossbar architectures and the significant resistance variations of memristors to develop an on-chip memristive device based strong PUF (mrSPUF). Our novel architecture demonstrates desirable characteristics of PUFs, including uniqueness, reliability, and large number of challenge-response pairs (CRPs) and desirable characteristics of strong PUFs. More significantly, in contrast to most existing PUFs, our PUF can act as a reconfigurable PUF (rPUF) without additional hardware and is of benefit to applications needing revocation or update of secure key information.

Enhanced challenge‐response set and secure usage scenarios for ordering‐based ring oscillator‐physical unclonable functions

The number of applicable challenge–response pairs (CRPs) in physical unclonable functions (PUFs) is critical especially for authentication protocols in security systems. Ideally, full read-out of all CRPs should be infeasible and CRPs should be independent from each other for a highly secure system. CRP concept is not defined in ordering-based ring oscillator (RO) PUFs presented in the literature. In this paper, the authors propose two methods for enhanced CRP set in ordering-based RO-PUFs and analyse their performance in terms of uniqueness and area efficiency. Next, they propose three secure usage scenarios based on enhanced CRP set methods, preventing the CRPs from leaking information about each other. With the proposed systems, 100% robust, area and power efficient and secure PUF structures with exponential number of CRPs become possible that are very convenient especially for authentication protocols.

PUF Modeling Attacks on Simulated and Silicon Data

We discuss numerical modeling attacks on several proposed strong physical unclonable functions (PUFs). Given a set of challenge-response pairs (CRPs) of a Strong PUF, the goal of our attacks is to construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. If successful, this algorithm can subsequently impersonate the Strong PUF, and can be cloned and distributed arbitrarily. It breaks the security of any applications that rest on the Strong PUF's unpredictability and physical unclonability. Our method is less relevant for other PUF types such as Weak PUFs. The Strong PUFs that we could attack successfully include standard Arbiter PUFs of essentially arbitrary sizes, and XOR Arbiter PUFs, Lightweight Secure PUFs, and Feed-Forward Arbiter PUFs up to certain sizes and complexities. We also investigate the hardness of certain Ring Oscillator PUF architectures in typical Strong PUF applications. Our attacks are based upon various machine learning techniques, including a specially tailored variant of logistic regression and evolution strategies. Our results are mostly obtained on CRPs from numerical simulations that use established digital models of the respective PUFs. For a subset of the considered PUFs-namely standard Arbiter PUFs and XOR Arbiter PUFs-we also lead proofs of concept on silicon data from both FPGAs and ASICs. Over four million silicon CRPs are used in this process. The performance on silicon CRPs is very close to simulated CRPs, confirming a conjecture from earlier versions of this work. Our findings lead to new design requirements for secure electrical Strong PUFs, and will be useful to PUF designers and attackers alike.

Applications of High-Capacity Crossbar Memories in Cryptography

This paper proposes a new approach for the construction of highly secure physical unclonable functions (PUFs). Instead of using systems with medium information content and high readout rates, we suggest to maximize the information content of the PUF while strongly reducing its readout frequency. We show that special, passive crossbar arrays with a very large random information content and inherently limited readout speed are suited to implement our approach. They can conceal sensitive information over long time periods and can be made secure against invasive physical attacks. To support our feasibility study, circuit-level simulations and experimental data are presented. Our design allows the first PUFs that are secure against computationally unrestricted adversaries, and which remain so in the face of weeks or even years of uninterrupted adversarial access. We term the new design principle a “SHIC PUF,” where the acronym SHIC stands for super high information content.