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

Very-Large-Scale-Integration Circuit Techniques in Internet-of-Things Applications

Heading towards the era of Internet-of-things (IoT) means both opportunity and challenge for the circuit-design community. In a system where billions of devices are equipped with the ability to sense, compute, communicate with each other and perform tasks in a coordinated manner, security and power management are among the most critical challenges. Physically unclonable function (PUF) emerges as an important security primitive in hardware-security applications; it provides an object-specific physical identifier hidden within the intrinsic device variations, which is hard to expose and reproduce by adversaries. Yet, designing a compact PUF robust to noise, temperature and voltage remains a challenge. This thesis presents a novel PUF design approach based on a pair of ultra-compact analog circuits whose output is proportional to absolute temperature. The proposed approach is demonstrated through two works: (1) an ultra-compact and robust PUF based on voltage-compensated proportional-to-absolute-temperature voltage generators that occupies 8.3× less area than the previous work with the similar robustness and twice the robustness of the previously most compact PUF design and (2) a technique to transform a 6T-SRAM array into a robust analog PUF with minimal overhead. In this work, similar circuit topology is used to transform a preexisting on-chip SRAM into a PUF, which further reduces the area in (1) with no robustness penalty. In this thesis, we also explore techniques for power management circuit design. Energy harvesting is an essential functionality in an IoT sensor node, where battery replacement is cost-prohibitive or impractical. Yet, existing energy-harvesting power management units (EH PMU) suffer from efficiency loss in the two-step voltage conversion: harvester-to-battery and battery-to-load. We propose an EH PMU architecture with hybrid energy storage, where a capacitor is introduced in addition to the battery to serve as an intermediate energy buffer to minimize the battery involvement in the system energy flow. Test-case measurements show as much as a 2.2× improvement in the end-to-end energy efficiency. In contrast, with the drastically reduced power consumption of IoT nodes that operates in the sub-threshold regime, adaptive dynamic voltage scaling (DVS) for supply-voltage margin removal, fully on-chip integration and high power conversion efficiency (PCE) are required in PMU designs. We present a PMU–load co-design based on a fully integrated switched-capacitor DC-DC converter (SC-DC) and hybrid error/replica-based regulation for a fully digital PMU control. The PMU is integrated with a neural spike processor (NSP) that achieves a record-low power consumption of 0.61 µW for 96 channels. A tunable replica circuit is added to assist the error regulation and prevent loss of regulation. With automatic energy-robustness co-optimization, the PMU can set the SC-DC’s optimal conversion ratio and switching frequency. The PMU achieves a PCE of 77.7% (72.2%) at VIN = 0.6 V (1 V) and at the NSP’s margin-free operating point

Flash-based security primitives: Evolution, challenges and future directions

Over the last two decades, hardware security has gained increasing attention in academia and industry. Flash memory has been given a spotlight in recent years, with the question of whether or not it can prove useful in a security role. Because of inherent process variation in the characteristics of flash memory modules, they can provide a unique fingerprint for a device and have thus been proposed as locations for hardware security primitives. These primitives include physical unclonable functions (PUFs), true random number generators (TRNGs), and integrated circuit (IC) counterfeit detection. In this paper, we evaluate the efficacy of flash memory-based security primitives and categorize them based on the process variations they exploit, as well as other features. We also compare and evaluate flash-based security primitives in order to identify drawbacks and essential design considerations. Finally, we describe new directions, challenges of research, and possible security vulnerabilities for flash-based security primitives that we believe would benefit from further exploration

Secure MQTT PUF-Based Key Exchange Protocol for Smart Healthcare

Replay and eavesdropping attacks threaten the information security that is held by smart healthcare devices. An authenticated key exchange method to provide cryptography sessions is the best way to provide information security and secure authentication. However, smart healthcare devices do not have sufficient computation to perform heavy cryptography processes due to the limitations of the embedded devices used. We propose an authenticated key exchange protocol based on a physical unclonable function (PUF). The proposed protocol aimed to countermeasure from replay and eavesdropping attacks. We designed our protocol with one handshake process and three authentication processes. We evaluated our proposed protocol using Tamarin Prover. From the results of the evaluation, our proposed protocol can exchange properties correctly between communication actors and is valid in proving each lemma in eavesdropping and replay attacks

A PUF based Lightweight Hardware Security Architecture for IoT

With an increasing number of hand-held electronics, gadgets, and other smart devices, data is present in a large number of platforms, thereby increasing the risk of security, privacy, and safety breach than ever before. Due to the extreme lightweight nature of these devices, commonly referred to as IoT or `Internet of Things\u27, providing any kind of security is prohibitive due to high overhead associated with any traditional and mathematically robust cryptographic techniques. Therefore, researchers have searched for alternative intuitive solutions for such devices. Hardware security, unlike traditional cryptography, can provide unique device-specific security solutions with little overhead, address vulnerability in hardware and, therefore, are attractive in this domain. As Moore\u27s law is almost at its end, different emerging devices are being explored more by researchers as they present opportunities to build better application-specific devices along with their challenges compared to CMOS technology. In this work, we have proposed emerging nanotechnology-based hardware security as a security solution for resource constrained IoT domain. Specifically, we have built two hardware security primitives i.e. physical unclonable function (PUF) and true random number generator (TRNG) and used these components as part of a security protocol proposed in this work as well. Both PUF and TRNG are built from metal-oxide memristors, an emerging nanoscale device and are generally lightweight compared to their CMOS counterparts in terms of area, power, and delay. Design challenges associated with designing these hardware security primitives and with memristive devices are properly addressed. Finally, a complete security protocol is proposed where all of these different pieces come together to provide a practical, robust, and device-specific security for resource-limited IoT systems

SCAN CHAIN BASED HARDWARE SECURITY

Hardware has become a popular target for attackers to hack into any computing and communication system. Starting from the legendary power analysis attacks discovered 20 years ago to the recent Intel Spectre and Meltdown attacks, security vulnerabilities in hardware design have been exploited for malicious purposes. With the emerging Internet of Things (IoT) applications, where the IoT devices are extremely resource constrained, many proven secure but computational expensive cryptography protocols cannot be applied on such devices. Thus there is an urgent need to understand the hardware vulnerabilities and develop cost effective mitigation methods. One established field in the semiconductor and integrated circuit (IC) industry, known as IC test, has the goal of ensuring that fabricated ICs are free of manufacturing defects and perform the required functionalities. Testing is essential to isolate faulty chips from good ones. The concept of design for test (DFT) has been integrated in the commercial IC design and fabrication process for several decades. Scan chain, which provides test engineer access to all the flip flops in the chip through the scan in (SI) and scan out (SO) ports, is the backbone of industrial testing methods and can be found in almost all the modern designs. In addition to IC testing, scan chain has found applications in intellectual property (IP) protection and IC identification. However, attackers can also leverage the controllability and observability of scan chain as a side channel to break systems such as cryptographic chips. This dissertation addresses these two important security problems by proposing (1) a practical scan chain based security primitive for IP protection and (2) a partial scan chain framework that can mitigate all the existing scan based attacks. First, we observe the fact that each D-flip-flop has two output ports, Q and Q’, designed to simplify the logic and has been used to reduce the power consumption for IC test. The availability of both Q and Q’ ports provide the opportunity for IP protection. More specifically, we can generate a digital fingerprint by selecting different connection styles between adjacent scan cells during the design of scan chain. This method has two major advantages: fingerprints are created as a post-silicon procedure and therefore there will be little fabrication overhead; altering the connection style requires the modification of test vectors for each fingerprinted IP and thus enables a non-intrusive fingerprint verification method. This addresses the overhead and detectability problems, two of the most challenging problems of designing practical IP fingerprinting techniques in the past two decades. Combined with the recently developed reconfigurable scan networks (RSNs) that are popular for embedded and IoT devices, we design an IC identification (ID) scheme utilizing the different connection styles. We perform experiments on standard benchmarks to demonstrate that our approach has low design overhead. We also conduct security analysis to show that such fingerprints and IC IDs are robust against various attacks. In the second part of this dissertation, we consider the scan chain side channel attack, which has been reported as one of the most severe side channel attacks to modern secure systems. We argue that the current countermeasures are restricted to the requirement of providing direct SI and SO for testing and thus suffers the vulnerability of leaving this side channel open to the attackers as well. Therefore, we propose a novel public-private partial scan chain based approach with the basic idea of removing the flip flops that store sensitive information from the scan chain. This will eliminate the scan chain side channel, but it also limits IC test. The key contribution in our proposed public-private partial scan chain design is that it can keep the full test coverage while providing security to the scan chain. This is achieved by chaining the removed flip flops into one or more private partial scan chains and adding protections to the SI and SO ports of such chains. Unlike the traditional partial scan design which not only fails to provide full fault coverage, but also incur huge overhead in test time and test vector generation time, we propose a set of techniques to ensure that the desired test vectors can be entered into the system efficiently. These techniques include test vector reordering, test vector reusing, and test vector generation based on a novel finite state machine (FSM) structure we have invented. On the other hand, to enable the test engineers the ability to observe the test output to diagnose the chip while not leaking information to the attackers, we propose two lightweight mechanisms, one based on linear feedback shift register (LFSR) and the other one based on configurable physical unclonable function (PUF). Finally, we discuss a protocol on how in-field test can be realized using our public-private partial scan chain. We conduct experiments with industrial scan design tools to demonstrate that the required hardware in our approach has negligible area overhead and gives full test coverage with reduced test time and does not need to re-generate test vectors. In sum, this dissertation focuses on the role of scan chain, a conventional design for test facility, in hardware security. We show that scan chain features can be leveraged to create practical IP protection techniques including IP watermarking and fingerprinting as well as IC identification and authentication. We also propose a novel public-private partial scan design principle to close the scan chain side channel to the attackers. Through this dissertation work, we demonstrate that it is possible to develop highly practical scan chain based techniques that can benefit both the community of IC test and hardware security

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

Practical Lightweight Security: Physical Unclonable Functions and the Internet of Things

In this work, we examine whether Physical Unclonable Functions (PUFs) can act as lightweight security mechanisms for practical applications in the context of the Internet of Things (IoT). In order to do so, we first discuss what PUFs are, and note that memory-based PUFs seem to fit the best to the framework of the IoT. Then, we consider a number of relevant memory-based PUF designs and their properties, and evaluate their ability to provide security in nominal and adverse conditions. Finally, we present and assess a number of practical PUF-based security protocols for IoT devices and networks, in order to confirm that memory-based PUFs can indeed constitute adequate security mechanisms for the IoT, in a practical and lightweight fashion. More specifically, we first consider what may constitute a PUF, and we redefine PUFs as inanimate physical objects whose characteristics can be exploited in order to obtain a behaviour similar to a highly distinguishable (i.e., “(quite) unique”) mathematical function. We note that PUFs share many characteristics with biometrics, with the main difference being that PUFs are based on the characteristics of inanimate objects, while biometrics are based on the characteristics of humans and other living creatures. We also note that it cannot really be proven that PUFs are unique per instance, but they should be considered to be so, insofar as (human) biometrics are also considered to be unique per instance. We, then, proceed to discuss the role of PUFs as security mechanisms for the IoT, and we determine that memory-based PUFs are particularly suited for this function. We observe that the IoT nowadays consists of heterogeneous devices connected over diverse networks, which include both high-end and resource-constrained devices. Therefore, it is essential that a security solution for the IoT is not only effective, but also highly scalable, flexible, lightweight, and cost-efficient, in order to be considered as practical. To this end, we note that PUFs have been proposed as security mechanisms for the IoT in the related work, but the practicality of the relevant security mechanisms has not been sufficiently studied. We, therefore, examine a number of memory-based PUFs that are implemented using Commercial Off-The-Shelf (COTS) components, and assess their potential to serve as acceptable security mechanisms in the context of the IoT, not only in terms of effectiveness and cost, but also under both nominal and adverse conditions, such as ambient temperature and supply voltage variations, as well as in the presence of (ionising) radiation. In this way, we can determine whether memory-based PUFs are truly suitable to be used in the various application areas of the IoT, which may even involve particularly adverse environments, e.g., in IoT applications involving space modules and operations. Finally, we also explore the potential of memory-based PUFs to serve as adequate security mechanisms for the IoT in practice, by presenting and analysing a number of cryptographic protocols based on these PUFs. In particular, we study how memory-based PUFs can be used for key generation, as well as device identification, and authentication, their role as security mechanisms for current and next-generation IoT devices and networks, and their potential for applications in the space segment of the IoT and in other adverse environments. Additionally, this work also discusses how memory-based PUFs can be utilised for the implementation of lightweight reconfigurable PUFs that allow for advanced security applications. In this way, we are able to confirm that memory-based PUFs can indeed provide flexible, scalable, and efficient security solutions for the IoT, in a practical, lightweight, and inexpensive manner

Intrinsic Functions for Securing CMOS Computation: Variability, Modeling and Noise Sensitivity

A basic premise behind modern secure computation is the demand for lightweight cryptographic primitives, like identifier or key generator. From a circuit perspective, the development of cryptographic modules has also been driven by the aggressive scalability of complementary metal-oxide-semiconductor (CMOS) technology. While advancing into nano-meter regime, one significant characteristic of today\u27s CMOS design is the random nature of process variability, which limits the nominal circuit design. With the continuous scaling of CMOS technology, instead of mitigating the physical variability, leveraging such properties becomes a promising way. One of the famous products adhering to this double-edged sword philosophy is the Physically Unclonable Functions (PUFs), which extract secret keys from uncontrollable manufacturing variability on integrated circuits (ICs). However, since PUFs take advantage of microscopic process variations, thus many specialized issues including variability, modeling attacks and noise sensitivity need to be considered and addressed. In this dissertation, we present our recent work on PUF based secure computation from three aspects: variability, modeling and noise sensitivity, which are deemed the foundations of our study. Moreover, we found that the three factors coordinate with each other in our study, for example, the modeling technique can be utilized to improve the unsatisfied reliability caused by noise sensitivity, quantifying the variability can effectively eliminate the impact from noise, and modeling can help with characterizing the physical variability precisely