FPGA-Based PUF Designs: A Comprehensive Review and Comparative Analysis

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.publishedVersio

Emerging physical unclonable functions with nanotechnology

Physical unclonable functions (PUFs) are increasingly used for authentication and identification applications as well as the cryptographic key generation. An important feature of a PUF is the reliance on minute random variations in the fabricated hardware to derive a trusted random key. Currently, most PUF designs focus on exploiting process variations intrinsic to the CMOS technology. In recent years, progress in emerging nanoelectronic devices has demonstrated an increase in variation as a consequence of scaling down to the nanoregion. To date, emerging PUFs with nanotechnology have not been fully established, but they are expected to emerge. Initial research in this area aims to provide security primitives for emerging integrated circuits with nanotechnology. In this paper, we review emerging nanotechnology-based PUFs

TI-PUF: Toward Side-Channel Resistant Physical Unclonable Functions

One of the main motivations behind introducing PUFs was their ability to resist physical attacks. Among them, cloning was the major concern of related scientific literature. Several primitive PUF designs have been introduced to the community, and several machine learning attacks have been shown capable to model such constructions. Although a few works have expressed how to make use of Side-Channel Analysis (SCA) leakage of PUF constructions to significantly improve the modeling attacks, little attention has been payed to provide corresponding countermeasures. In this paper, we present a generic technique to operate any PUF primitive in an SCA-secure fashion. We, for the first time, make it possible to apply a provably-secure masking countermeasure – Threshold Implementation (TI) – on a strong PUF design. As a case study, we concentrate on the Interpose PUF, and based on practical experiments on an FPGA prototype, we demonstrate the ability of our construction to prevent the recovery of intermediate values through SCA measurements

Machine-Learning Attacks on PolyPUFs, OB-PUFs, RPUFs, LHS-PUFs, and PUF–FSMs

A physically unclonable function (PUF) is a circuit of which the input–output behavior is designed to be sensitive to the random variations of its manufacturing process. This building block hence facilitates the authentication of any given device in a population of identically laid-out silicon chips, similar to the biometric authentication of a human. The focus and novelty of this work is the development of efficient impersonation attacks on the following five Arbiter PUF–based authentication protocols: (1) the so-called PolyPUF protocol of Konigsmark, Chen, and Wong, as published in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems in 2016, (2) the so-called OB-PUF protocol of Gao, Li, Ma, Al-Sarawi, Kavehei, Abbott, and Ranasinghe, as presented at the IEEE conference PerCom 2016, (3) the so-called RPUF protocol of Ye, Hu, and Li, as presented at the IEEE conference AsianHOST 2016, (4) the so-called LHS-PUF protocol of Idriss and Bayoumi, as presented at the IEEE conference RFID-TA 2017, and (5) the so-called PUF–FSM protocol of Gao, Ma, Al-Sarawi, Abbott, and Ranasinghe, as published in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems in 2018. The common flaw of all five designs is that the use of lightweight obfuscation logic provides insufficient protection against machine learning attacks

Lightweight PUF-Based Gate Replacement Technique to Reduce Leakage of Information through Power Profile Analysis

The major challenge faced by electronic device designers is to defend the system from attackers and malicious modules called Hardware Trojans and to deliver a secured design. Although there are many cryptographic preventive measures in place adversaries find different ways to attack the device. Differential Power Analysis (DPA) attack is a type of Side Channel Attacks, used by an attacker to analyze the power leakage in the circuit, through which the functionality of the circuit is extracted. To overcome this, a lightweight approach is proposed in this paper using, Wave Dynamic Differential Logic (WDDL) technique, without incurring any additional resource cost and power. The primary objective of WDDL is to make the power consumption constant of an entire circuit by restricting the leakage power. The alternate strategy used by an adversary is to leak the information through reverse engineering. The proposed work avoids this by using a bit sequencer and a modified butterfly PUF based randomizing architecture. A modified version of butterfly PUF is also proposed in this paper, and from various qualitative tests performed it is evident that this PUF can prevent information leakage. This work is validated on ISCAS 85, ISCAS 89 benchmark circuits and the results obtained indicate that the difference in leakage power is found to be very marginal

Hardware security design from circuits to systems

The security of hardware implementations is of considerable importance, as even the most secure and carefully analyzed algorithms and protocols can be vulnerable in their hardware realization. For instance, numerous successful attacks have been presented against the Advanced Encryption Standard, which is approved for top secret information by the National Security Agency. There are numerous challenges for hardware security, ranging from critical power and resource constraints in sensor networks to scalability and automation for large Internet of Things (IoT) applications. The physically unclonable function (PUF) is a promising building block for hardware security, as it exposes a device-unique challenge-response behavior which depends on process variations in fabrication. It can be used in a variety of applications including random number generation, authentication, fingerprinting, and encryption. The primary concerns for PUF are reliability in presence of environmental variations, area and power overhead, and process-dependent randomness of the challenge-response behavior. Carbon nanotube field-effect transistors (CNFETs) have been shown to have excellent electrical and unique physical characteristics. They are a promising candidate to replace silicon transistors in future very large scale integration (VLSI) designs. We present the Carbon Nanotube PUF (CNPUF), which is the first PUF design that takes advantage of unique CNFET characteristics. CNPUF achieves higher reliability against environmental variations and increases the resistance against modeling attacks. Furthermore, CNPUF has a considerable power and energy reduction in comparison to previous ultra-low power PUF designs of 89.6% and 98%, respectively. Moreover, CNPUF allows a power-security tradeoff in an extended design, which can greatly increase the resilience against modeling attacks. Despite increasing focus on defenses against physical attacks, consistent security oriented design of embedded systems remains a challenge, as most formalizations and security models are concerned with isolated physical components or a high-level concept. Therefore, we build on existing work on hardware security and provide four contributions to system-oriented physical defense: (i) A system-level security model to overcome the chasm between secure components and requirements of high-level protocols; this enables synergy between component-oriented security formalizations and theoretically proven protocols. (ii) An analysis of current practices in PUF protocols using the proposed system-level security model; we identify significant issues and expose assumptions that require costly security techniques. (iii) A System-of-PUF (SoP) that utilizes the large PUF design-space to achieve security requirements with minimal resource utilization; SoP requires 64% less gate-equivalent units than recently published schemes. (iv) A multilevel authentication protocol based on SoP which is validated using our system-level security model and which overcomes current vulnerabilities. Furthermore, this protocol offers breach recognition and recovery. Unpredictability and reliability are core requirements of PUFs: unpredictability implies that an adversary cannot sufficiently predict future responses from previous observations. Reliability is important as it increases the reproducibility of PUF responses and hence allows validation of expected responses. However, advanced machine-learning algorithms have been shown to be a significant threat to the practical validity of PUFs, as they can accurately model PUF behavior. The most effective technique was shown to be the XOR-based combination of multiple PUFs, but as this approach drastically reduces reliability, it does not scale well against software-based machine-learning attacks. We analyze threats to PUF security and propose PolyPUF, a scalable and secure architecture to introduce polymorphic PUF behavior. This architecture significantly increases model-building resistivity while maintaining reliability. An extensive experimental evaluation and comparison demonstrate that the PolyPUF architecture can secure various PUF configurations and is the only evaluated approach to withstand highly complex neural network machine-learning attacks. Furthermore, we show that PolyPUF consumes less energy and has less implementation overhead in comparison to lightweight reference architectures. Emerging technologies such as the Internet of Things (IoT) heavily rely on hardware security for data and privacy protection. The outsourcing of integrated circuit (IC) fabrication introduces diverse threat vectors with different characteristics, such that the security of each device has unique focal points. Hardware Trojan horses (HTH) are a significant threat for IoT devices as they process security critical information with limited resources. HTH for information leakage are particularly difficult to detect as they have minimal footprint. Moreover, constantly increasing integration complexity requires automatic synthesis to maintain the pace of innovation. We introduce the first high-level synthesis (HLS) flow that produces a threat-targeted and security enhanced hardware design to prevent HTH injection by a malicious foundry. Through analysis of entropy loss and criticality decay, the presented algorithms implement highly resource-efficient targeted information dispersion. An obfuscation flow is introduced to camouflage the effects of dispersion and reduce the effectiveness of reverse engineering. A new metric for the combined security of the device is proposed, and dispersion and obfuscation are co-optimized to target user-supplied threat parameters under resource constraints. The flow is evaluated on existing HLS benchmarks and a new IoT-specific benchmark, and shows significant resource savings as well as adaptability. The IoT and cloud computing rely on strong confidence in security of confidential or highly privacy sensitive data. As (differential) power attacks can take advantage of side-channel leakage to expose device-internal secrets, side-channel leakage is a major concern with ongoing research focus. However, countermeasures typically require expert-level security knowledge for efficient application, which limits adaptation in the highly competitive and time-constrained IoT field. We address this need by presenting the first HLS flow with primary focus on side-channel leakage reduction. Minimal security annotation to the high-level C-code is sufficient to perform automatic analysis of security critical operations with corresponding insertion of countermeasures. Additionally, imbalanced branches are detected and corrected. For practicality, the flow can meet both resource and information leakage constraints. The presented flow is extensively evaluated on established HLS benchmarks and a general IoT benchmark. Under identical resource constraints, leakage is reduced between 32% and 72% compared to the baseline. Under leakage target, the constraints are achieved with 31% to 81% less resource overhead

Model Building and Security Analysis of PUF-Based Authentication

In the context of hardware systems, authentication refers to the process of confirming the identity and authenticity of chip, board and system components such as RFID tags, smart cards and remote sensors. The ability of physical unclonable functions (PUF) to provide bitstrings unique to each component can be leveraged as an authentication mechanism to detect tamper, impersonation and substitution of such components. However, authentication requires a strong PUF, i.e., one capable of producing a large, unique set of bits per device, and, unlike secret key generation for encryption, has additional challenges that relate to machine learning attacks, protocol attacks and constraints on device resources. We describe the requirements for PUF-based authentication, and present a PUF primitive and protocol designed for authentication in resource constrained devices. Our experimental results are derived from a 28 nm Xilinx FPGA. In the authentication scenario, strong PUFs are required since the adversary could collect a subset of challenges and response pairsto build a model and predict the responses for unseen challenges. Therefore, strong PUFs need to provide exponentially large challenge space and be resilient to model building attacks. We investigate the security properties of a Hardware-embedded Delay PUF called HELP which leverages within-die variations in path delays within a hardware-implemented macro (functional unit) as the entropy source. Several features of the HELP processing engine significantly improve its resistance to model-building attacks. We also investigate a novel technique that significantly improves the statistically quality of the generated bitstring for HELP. Stability across environmental variations such as temperature and voltage, is critically important for Physically Unclonable Functions (PUFs). Nearly all existing PUF systems to date need a mechanism to deal with “bit flips” when exact regeneration of the bitstring is required, e.g., for cryptographic applications. Error correction (ECC) and error avoidance schemes have been proposed but both of these require helper data to be stored for the regeneration process. Unfortunately, helper data adds time and area overhead to the PUF system and provides opportunities for adversaries to reverse engineer the secret bitstring. We propose a non-volatile memory-based (NVM) PUF that is able to avoid bit flips without requiring any type of helper data. We describe the technique in the context of emerging nano-devices, in particular, resistive random access memory (Memristor) cells, but the methodology is applicable to any type of NVM including Flash

Design of hardware-based security solutions for interconnected systems

Among all the different research lines related to hardware security, there is a particular topic that strikingly attracts attention. That topic is the research regarding the so-called Physical Unclonable Functions (PUF). The PUFs, as can be seen throughout the Thesis, present the novel idea of connecting digital values uniquely to a physical entity, just as human biometrics does, but with electronic devices. This beautiful idea is not free of obstacles, and is the core of this Thesis. It is studied from different angles in order to better understand, in particular, SRAM PUFs, and to be able to integrate them into complex systems that expand their potential. During Chapter 1, the PUFs, their properties and their main characteristics are defined. In addition, the different types of PUFs, and their main applications in the field of security are also summarized. Once we know what a PUF is, and the types of them we can find, throughout Chapter 2 an exhaustive analysis of the SRAM PUFs is carried out, given the wide availability of SRAMs today in most electronic circuits (which dramatically reduces the cost of deploying any solution). An algorithm is proposed to improve the characteristics of SRAM PUFs, both to generate identifiers and to generate random numbers, simultaneously. The results of this Chapter demonstrates the feasibility of implementing the algorithm, so in the following Chapters it is explored its integration in both hardware and software systems. In Chapter 3 the hardware design and integration of the algorithm introduced in Chapter 2 is described. The design is presented together with some examples of use that demonstrate the possible practical realizations in VLSI designs. In an analogous way, in Chapter 4 the software design and integration of the algorithm introduced in Chapter 2 is described. The design is presented together with some examples of use that demonstrate the possible practical realizations in low-power IoT devices. The algorithm is also described as part of a secure firmware update protocol that has been designed to be resistant to most current attacks, ensuring the integrity and trustworthiness of the updated firmware.In Chapter 5, following the integration of PUF-based solutions into protocols, PUFs are used as part of an authentication protocol that uses zero-knowledge proofs. The cryptographic protocol is a Lattice-based post-quantum protocol that guarantees the integrity and anonymity of the identity generated by the PUF. This type of architecture prevents any type of impersonation or virtual copy of the PUF, since this is unknown and never leaves the device. Specifically, this type of design has been carried out with the aim of having traceability of identities without ever knowing the identity behind, which is very interesting for blockchain technologies. Finally, in Chapter 6 a new type of PUF, named as BPUF (Behavioral and Physical Unclonable Function), is proposed and analyzed according to the definitions given in Chapter 1. This new type of PUF significantly changes the metrics and concepts to which we were used to in previous Chapters. A new multi-modal authentication protocol is presented in this Chapter, taking advantage of the challenge-response tuples of BPUFs. An example of BPUFs is illustrated with SRAMs. A proposal to integrate the BPUFs described in Chapter 6 into the protocol of Chapter 5, as well as the final remarks of the Thesis, can be found in Chapter 7