Reliable, Secure, Efficient Physical Unclonable Functions

A new concept for Physical Unclonable Functions (PUFs), the Mirror PUF, is proposed. The Mirror PUF can be applied to existing preselected PUF circuits by post-processing the preselection test results and has the potential to double the number of effective bits, with no additional area at the bit-cell level. The Mirror PUF utilizes a preselection test, which measures the amount of mismatch within the PUF cell. This data is generally used to determine the mask for a conventional PUF. Here, it is used as an entropy source that is not correlated to the original response of the PUF. Bit-cells with low mismatch are considered as a ‘0’ and cells with high mismatch as a ‘1’. A systematic method is shown for identifying unstable bits in the Mirror PUF response. It classifies the cells to ‘low’, ‘medium’ and ‘high’ mismatch, such that medium mismatch bits are considered as unstable and masked from the response. The concept was applied to a 65nm Si implementation of the Capacitive Tilt PUF (Shifman et al., 2020). All of the unstable cells of the Mirror PUF, except for 0.03%, were identified and masked, with a worst-case corner Bit Error-Rate (BER) of only 2.35E-5 and 0.00026% erroneous responses across all corners. The application of the Mirror PUF to the Capacitive tilt PUF increased the number of stable response bits by 66%. No observable correlation was found between the responses of the original PUF and the Mirror PUF.

The use of physically unclonable functions (PUFs) as a new cryptographic technique is gaining attention. Challenge-response authentication and key generation (key storage) are well known as major applications using PUFs. When PUFs are applied to these applications, min-entropy estimation is essential. The min-entropy is a measure of the lower bound of the unpredictability of PUF responses. Many studies have estimated the min-entropy of PUFs, and several of these studies dealt with PUFs with independent and identically distributed (IID) PUF responses. Few studies have focused on non-IID PUFs. One reason is that some causes of entropy loss are complicatedly intertwined, and the entropy estimation of non-IID PUFs is hard. Thus, it is first necessary to break down the intertwined causes to estimate min-entropy. In this paper, we present typical causes of entropy loss during PUF implementation and propose a cause analysis method using the Inter-Hamming distance (HD), which is one of major performance metrics of PUFs. And the proposed method was applied to prototyped PUFs designed with a 180-nm CMOS process. We demonstrate that the causes of entropy loss on each PUF can be broken down according to the analysis results.

Physical unclonable functions (PUFs) are primitives that generate high-entropy, tamper resistant bits for use in secure systems. For applications such as cryptographic key generation, the PUF response bits must be highly reliable, consistent across multiple evaluations under voltage and temperature variations. Conventionally, error correcting codes (ECC) have been used to improve response reliability, but these techniques have significant area, power, and delay overheads and are vulnerable to information leakage. In this work, we present a highly-reliable, PUF-based, cryptographic key generator that uses no ECC, but instead uses built-in self-test to determine which PUF bits are reliable and only uses those bits for key generation. We implemented a prototype of the key generator in a 65nm bulk CMOS testchip. The key generator generates 1213 bits in an area of <;50k/μm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> with a measured bit error rate of <; 5 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sub> 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-9</sup> in both the nominal and worst case corners (100k measurements each). This is equivalent to a 128-bit key failure rate of <; 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> . The system can generate a 128-bit key in 1.15μs. Finally, we present a realization of a “strong”-PUF that uses 128 of these highly reliable bits in conjunction with an Advanced Encryption Standard (AES) cryptographic primitive and has a response time of 40ns and is realized in an area of 84k/μm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

FPGA-based Physical Unclonable Functions (PUFs) have emerged as a viable alternative to permanent key storage by turning inaccuracies during the manufacturing process of a chip into a unique, FPGA-intrinsic secret. However, many fixed PUF designs may suffer from unsatisfactory statistical properties in terms of uniqueness, uniformity, and robustness. Moreover, a PUF signature may alter over time due to aging or changing operating conditions, rendering a PUF insecure in the worst case. As a remedy, we propose CHOICE, a novel class of FPGA-based PUF designs with tunable uniqueness and reliability characteristics. By the use of addressable shift registers available on an FPGA, we show that a wide configuration space for adjusting a device-specific PUF response is obtained without any sacrifice of randomness. In particular, we demonstrate the concept of address-tunable propagation delays, whereby we are able to increase or decrease the probability of obtaining 1’s in the PUF response. Experimental evaluations on a group of six 28 nm Xilinx Artix-7 FPGAs show that CHOICE PUFs provide a large range of configurations to allow a fine-tuning to an average uniqueness between 49% and 51%, while simultaneously achieving bit error rates below 1.5%, thus outperforming state-of-the-art PUF designs. Moreover, with only a single FPGA slice per PUF bit, CHOICE is one of the smallest PUF designs currently available for FPGAs.

We propose a scheme to prevent the machine learning (ML) attacks against physically unclonable functions (PUFs). A silicon PUF is a security primitive in a semiconductor chip that generates a unique identifier by exploiting device variations. However, some PUF implementations are vulnerable to ML attacks, in which an attacker tries to obtain the mathematical clone of the target PUF to predict its responses. Our scheme adds intentional noise to the responses to disturb ML by an attacker so that the clone fails to be authenticated, while the original PUF can still be correctly authenticated using an error correction code (ECC). The effectiveness of this scheme is not very obvious because the attacker can also use the ECC. We apply the countermeasure to n-XOR arbiter PUFs to investigate the feasibility of the proposed scheme. We explain the relationship between the prediction accuracy of the clone and the number of intentional noise bits. Our scheme can successfully distinguish a clone from the legitimate PUF in the case of 5-XOR PUF.

Several publications presented tamper-evident Physical Unclonable Functions (PUFs) for secure storage of cryptographic keys and tamper-detection. Unfortunately, previously published PUF-based key derivation schemes do not sufficiently take into account the specifics of the underlying application, i.e., an attacker that tampers with the physical parameters of the PUF outside of an idealized noise error model. This is a notable extension of existing schemes for PUF key derivation, as they are typically concerned about helper data leakage, i.e., by how much the PUF’s entropy is diminished when gaining access to its helper data. To address the specifics of tamper-evident PUFs, we formalize the aspect of tamper-sensitivity, thereby providing a new tool to rate by how much an attacker is allowed to tamper with the PUF. This complements existing criteria such as effective number of secret bits for entropy and failure rate for reliability. As a result, it provides a fair comparison among different schemes and independent of the PUF implementation, as its unit is based on the noise standard deviation of the underlying PUF measurement. To overcome the limitations of previous schemes, we then propose an Error-Correcting Code (ECC) based on the Lee metric, i.e., a distance metric well-suited to describe the distance between q-ary symbols as output from an equidistant quantization, i.e., a higher-order alphabet PUF. This novel approach is required, as the underlying symbols’ bits are not i.i.d. which hinders applying previous state-of-the-art approaches. We present the concept for our scheme and demonstrate its feasibility based on an empirical PUF distribution. The benefits of our approach are an increase by over 21% in effective secret bit compared to previous approaches based on equidistant quantization. At the same time, we improve tamper-sensitivity compared to an equiprobable quantization while ensuring similar reliability and entropy. Hence, this work opens up a new direction of how to interpret the PUF output and details a practically relevant scheme outperforming all previous constructions.

Field-programmable gate arrays (FPGAs) have firmly established themselves as dynamic platforms for the implementation of physical unclonable functions (PUFs). Their intrinsic reconfigurability and profound implications for enhancing hardware security make them an invaluable asset in this realm. This groundbreaking study not only dives deep into the universe of FPGA-based PUF designs but also offers a comprehensive overview coupled with a discerning comparative analysis. PUFs are the bedrock of device authentication and key generation and the fortification of secure cryptographic protocols. Unleashing the potential of FPGA technology expands the horizons of PUF integration across diverse hardware systems. We set out to understand the fundamental ideas behind PUF and how crucially important it is to current security paradigms. Different FPGA-based PUF solutions, including static, dynamic, and hybrid systems, are closely examined. Each design paradigm is painstakingly examined to reveal its special qualities, functional nuances, and weaknesses. We closely assess a variety of performance metrics, including those related to distinctiveness, reliability, and resilience against hostile threats. We compare various FPGA-based PUF systems against one another to expose their unique advantages and disadvantages. This study provides system designers and security professionals with the crucial information they need to choose the best PUF design for their particular applications. Our paper provides a comprehensive view of the functionality, security capabilities, and prospective applications of FPGA-based PUF systems. The depth of knowledge gained from this research advances the field of hardware security, enabling security practitioners, researchers, and designers to make wise decisions when deciding on and implementing FPGA-based PUF solutions.

Physically unclonable functions (PUFs) have been explored as lightweight hardware primitives for the purpose of realizing robust security via strong authentication or secure key/ID generation. PUF harness manufacturing process variations for the purpose of generating binary keys or binary functions. An ideal strong PUF is a binary function that maps an m-bit input challenge to an uniquen-bit output response, making it attractive for authentication applications. Unfortunately, real strong PUF implementations suffer from reliability issues where the same challenge may produce different responses in the presence of noise. To overcome this problem, strong PUF leverages the availability of exponential number of challenge-response pairs (CRPs). A successful authentication event requires acquiring multiple CRPs and applying a threshold. In contrast, weak PUFs produce limited keys and are required to be highly reliable. Multiple techniques have been developed to achieve the necessary reliability. An additional prerequisite for strong PUFs is resilience against model-building attacks (cloning) by an adversary, who has observed a few CRPs, to prevent successful prediction of future CRPs. In this work, we first illustrate a strong PUF design that re-purposes a weightless neural network (WNN). Second, we showcase the robustness of WNN-based strong PUFs with respect to machine learning attacks, while providing desirable uniqueness and reliability metrics. Finally, we employ an initial entropy source of highly reliable weak PUF bits mapped to weightless neural networks (WNNs) for the purpose of creating a near-ideal strong PUF in terms of reliability. Our results show that it is possible to create highly reliable WNN–based strong PUFs with < 65 % ML accuracy by using as few as 32 initial reliable weak PUF bits.

The proposed 8-Transistor (8T) Physically Unclonable Function (PUF), in conjunction with the power gating technique, can significantly accelerate a single evaluation cycle more than 100,000 times faster than a 6-Transistor (6T) Static Random-Access Memory (SRAM) PUF. The 8T PUF is built to swiftly eliminate data remanence and maximise physical mismatch. Moreover, a two-phase power gating module is devised to provide controllable power on/off cycles for the chosen PUF clusters in order to facilitate fast statistical measurements and curb the in-rush current. The architecture and hardware implementation of the power-gated PUF are developed to accommodate fast multiple evaluations of PUF Responses. The fast speed enables a new data processing method, which coordinates Dark-bit masking and Multiple Temporal Majority Voting (TMV) in different Process, Voltage and Temperature (PVT) corners or during field usage, hence greatly reducing the Bit Error Rate (BER) and the hardware penalty for error correction. The designs are based on the UMC 65 nm technology and aim to tape out an Application-Specific Integrated Circuit (ASIC) chip. Post-layout Monte Carlo (MC) simulations are performed with Cadence, and the extracted PUF Responses are processed with Matlab to evaluate the 8T PUF performance and statistical metrics for subsequent inclusion in PUF Responses, which comprise the novelty of this approach.

Embedded systems carry and process more and more sensitive information in untrusted environments, where an attacker can wiretap the external communication and also has unlimited physical access to the device. Cryptography protects systems against many of the threats and relies on the security of the cryptographic keys inside the system. Physical Unclonable Functions (PUFs) measure manufacturing variations inside integrated circuits, for example FPGAs, to generate a unique secret PUF response inside each device. Similar to deriving a biometric pattern from human features, the individual pattern inside an FPGA differs slightly from measurement to measurement. From these measurements, the PUF response is generated to derive a secure and reliable cryptographic key. The Ring-Oscillator (RO) PUF is a popular PUF type because of its high randomness and reliability. Frequencies of ROs are compared pairwise to derive one secret bit. So far, the reliability of RO PUFs was evaluated by counting bit flips in measured PUF responses. This work analyzes the distribution of frequency measurements to derive the behavior of the PUF. Analyzing the frequency distributions gives a more precise estimation of the PUF bit error rates than measuring the bit errors after the comparison of two oscillator frequencies. The evaluation of publicly available real world empirical FPGA data has shown that most error probabilities of RO PUF responses are so low that they cannot be measured in feasible time. For almost 200 evaluated FPGAs, more than 70% of the PUF outputs on every FPGA have bit error probabilities under 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-20</sup> . We can even ensure this error probability for over 60% of the PUF outputs after a practicable number of frequency measurements with a confidence of 99.9%. Index Terms-Physical Unclonable Functions (PUFs), Ring Oscillator PUF, FPGA, Statistics.

Lightweight implementation of security primitives, e.g., physical unclonable functions (PUFs) and true random number generator, in field programmable gate array (FPGA) is crucial replacement of the conventional decryption key stored in battery-backed random access memory or E-Fuses for the protection of field reconfigurable assets. A slice is the smallest reconfigurable logic block in an Xilinx FPGA. The entropy exploitable from each slice of an FPGA is an important factor for the design of security primitives. Previous research has shown that the locations of slices can impact the quality of delay-based PUF designs implemented on FPGAs. To investigate the effect of the placement of each single-bit PUF cell free from the routing resource constraint between slices, single-bit ring oscillator (RO) and identity-based PUF design (Pi-coPUF) cells that can each be fully fitted into a single slice are evaluated. To accurately evaluate their statistical performance, data from a large number of devices are required. To this end, 217 Xilinx Artix-7 FPGAs has been employed to provide a large-scale comprehensive analysis for the two designs. This is the first time single-slice disorder-based security entities have been investigated and compared on 28-nm Xilinx FPGA. Uniqueness, uniformity, correlation, reliability, bit-aliasing and min-entropy of each type of cell are evaluated for four different types of cell placement. Our experimental results corroborate that the location of both cell types in the FPGA affects their performances. For both cell types, the lower the correlation between devices, the higher the min-entropy and uniqueness. Overall, the min-entropy, correlation and uniqueness of PicoPUF are slightly higher than those of RO. Otherwise, the uniformity, bit-aliasing and reliability of the PicoPUF are slightly lower than those of the RO. Comparing the resource usage and metrics of the PicoPUF, ring oscillator PUF and some existing memory-based PUF implementations, PicoPUF stands out as a lightweight FPGA-based weak PUF design. The raw data for the PicoPUF design are made publicly available to enable the research community to use them for benchmarking and/or validation.

Physically Unclonable Function (PUF) designs proposed in the recent literature vary widely in diverse characteristics such as hardware resource requirement, reliability, entropy, and robustness against mathematical cloning. Most of the standalone PUF designs suffer from either poor performance profile or unacceptable resource-overhead. We present a novel PUF design paradigm, termed as PUF Composition, that utilizes smaller PUFs as design building blocks to define a “Composite PUF” having larger challenge-space and superior performance profile at reasonable resource-overhead. A formal framework for PUF composition based on a probabilistic model has also been developed to enable the Composite PUF designer to have a-priori estimate of the relative qualities of several composite PUF options, without actually implementing them physically. The notion of PUF composition, and the probabilistic model developed for delay-PUFs, have both been validated using Ring Oscillator PUF (ROPUF) and Arbiter PUF (APUF) on Xilinx Spartan-3 Field Programmable Gate Array (FPGA).

A Physical Unclonable Function (PUF) is often used to uniquely identify an integrated circuit by extracting its internal random differences using so-called Challenge Response Pairs (CRPs). As CRPs include unique information about the underlying hardware variations, PUF design is a promising approach to provide authentication and IP-protection capabilities. In this paper, an XOR-gate-based configurable Ring Oscillator (RO) PUF (denoted as XCRO PUF) is presented. This XCRO PUF can generate more CRPs compared with state-of-the-art PUF designs by using the same number of configurable logic blocks (CLBs) in an FPGA implementation. This design is implemented in the Xilinx Spartan-6 XC6SLX9 FPGAs with fixed locations for the XCROs (placed within a ring to improve its uniqueness). The XCRO PUF shows better uniqueness and reliability than other PUF designs. Moreover, a XCRO PUF consumes only 12.5% of the hardware resources to generate a 1-bit response compared with other CRO PUFs implemented in FPGA.

The use of physical unclonable functions (PUFs) to generate fingerprints for authentication of chips or larger electronic systems or for generation of internal cryptographic keys for data transfer is investigated. With the implementation of PUFs, each chip or electronic system has its own identity, which should prevent counterfeiting and &#x201C;night shift&#x201D; problems. There are various approaches to creating PUFs, and one of them is the so-called coating PUF, which would open the way to cost-effective and flexible protection during and after chip fabrication. In this work, we present two different capacitance measurement methods for fabricated PUF structures consisting of individual metal-oxide-semiconductor (MOS) capacitors. The goal is to obtain an easy and highly accurate measurement setup. Our fabricated PUF chips show an intended variation in capacitance and therefore generate characteristic fingerprints. We show that the parasitic capacitances and measurement variation are much smaller than the intended fluctuation of our PUF capacitances. This enables us to generate reliable and less error-prone fingerprints. Our presented measurement methods in combination with the technological PUF structures have shown to be accurate and reliable for flexible commercial application.

Physical unclonable functions (PUFs) are devices which are easily probed but difficult to predict. Optical PUFs have been discussed within the literature, with traditional optical PUFs typically using spatial light modulators, coherent illumination, and scattering volumes; however, these systems can be large, expensive, and difficult to maintain alignment in practical conditions. We propose and demonstrate a new kind of optical PUF based on computational imaging and compressive sensing to address these challenges with traditional optical PUFs. This work describes the design, simulation, and prototyping of this computational optical PUF (COPUF) that utilizes incoherent polychromatic illumination passing through an additively manufactured refracting optical polymer element. We demonstrate the ability to pass information through a COPUF using a variety of sampling methods, including the use of compressive sensing. The sensitivity of the COPUF system is also explored. We explore non-traditional PUF configurations enabled by the COPUF architecture. The double COPUF system, which employees two serially connected COPUFs, is proposed and analyzed as a means to authenticate and communicate between two entities that have previously agreed to communicate. This configuration enables estimation of a message inversion key without the calculation of individual COPUF inversion keys at any point in the PUF life cycle. Our results show that it is possible to construct inexpensive optical PUFs using computational imaging. This could lead to new uses of PUFs in places where electrical PUFs cannot be utilized effectively, as low cost tags and seals, and potentially as authenticating and communicating devices.