Circuit Techniques for Low-Power and Secure Internet-of-Things Systems

The coming of Internet of Things (IoT) is expected to connect the physical world to the cyber world through ubiquitous sensors, actuators and computers. The nature of these applications demand long battery life and strong data security. To connect billions of things in the world, the hardware platform for IoT systems must be optimized towards low power consumption, high energy efficiency and low cost. With these constraints, the security of IoT systems become a even more difficult problem compared to that of computer systems. A new holistic system design considering both hardware and software implementations is demanded to face these new challenges. In this work, highly robust and low-cost true random number generators (TRNGs) and physically unclonable functions (PUFs) are designed and implemented as security primitives for secret key management in IoT systems. They provide three critical functions for crypto systems including runtime secret key generation, secure key storage and lightweight device authentication. To achieve robustness and simplicity, the concept of frequency collapse in multi-mode oscillator is proposed, which can effectively amplify the desired random variable in CMOS devices (i.e. process variation or noise) and provide a runtime monitor of the output quality. A TRNG with self-tuning loop to achieve robust operation across -40 to 120 degree Celsius and 0.6 to 1V variations, a TRNG that can be fully synthesized with only standard cells and commercial placement and routing tools, and a PUF with runtime filtering to achieve robust authentication, are designed based upon this concept and verified in several CMOS technology nodes. In addition, a 2-transistor sub-threshold amplifier based "weak" PUF is also presented for chip identification and key storage. This PUF achieves state-of-the-art 1.65% native unstable bit, 1.5fJ per bit energy efficiency, and 3.16% flipping bits across -40 to 120 degree Celsius range at the same time, while occupying only 553 feature size square area in 180nm CMOS. Secondly, the potential security threats of hardware Trojan is investigated and a new Trojan attack using analog behavior of digital processors is proposed as the first stealthy and controllable fabrication-time hardware attack. Hardware Trojan is an emerging concern about globalization of semiconductor supply chain, which can result in catastrophic attacks that are extremely difficult to find and protect against. Hardware Trojans proposed in previous works are based on either design-time code injection to hardware description language or fabrication-time modification of processing steps. There have been defenses developed for both types of attacks. A third type of attack that combines the benefits of logical stealthy and controllability in design-time attacks and physical "invisibility" is proposed in this work that crosses the analog and digital domains. The attack eludes activation by a diverse set of benchmarks and evades known defenses. Lastly, in addition to security-related circuits, physical sensors are also studied as fundamental building blocks of IoT systems in this work. Temperature sensing is one of the most desired functions for a wide range of IoT applications. A sub-threshold oscillator based digital temperature sensor utilizing the exponential temperature dependence of sub-threshold current is proposed and implemented. In 180nm CMOS, it achieves 0.22/0.19K inaccuracy and 73mK noise-limited resolution with only 8865 square micrometer additional area and 75nW extra power consumption to an existing IoT system.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138779/1/kaiyuan_1.pd

Design and Evaluation of FPGA-based Hybrid Physically Unclonable Functions

A Physically Unclonable Function (PUF) is a new and promising approach to provide security for physical systems and to address the problems associated with traditional approaches. One of the most important performance metrics of a PUF is the randomness of its generated response, which is presented via uniqueness, uniformity, and bit-aliasing. In this study, we implement three known PUF schemes on an FPGA platform, namely SR Latch PUF, Basic RO PUF, and Anderson PUF. We then perform a thorough statistical analysis on their performance. In addition, we propose the idea of the Hybrid PUF structure in which two (or more) sources of randomness are combined in a way to improve randomness. We investigate two methods in combining the sources of randomness and we show that the second one improves the randomness of the response, significantly. For example, in the case of combining the Basic RO PUF and the Anderson PUF, the Hybrid PUF uniqueness is increased nearly 8%, without any pre-processing or post-processing tasks required. Two main categories of applications for PUFs have been introduced and analyzed: authentication and secret key generation. In this study, we introduce another important application for PUFs. In fact, we develop a secret sharing scheme using a PUF to increase the information rate and provide cheater detection capability for the system. We show that, using the proposed method, the information rate of the secret sharing scheme will improve significantly

Comprehensive Designs of Innovate Secure Hardware Devices against Machine Learning Attacks and Power Analysis Attacks

Hardware security is an innovate subject oriented from growing demands of cybersecurity and new information vulnerabilities from physical leakages on hardware devices. However, the mainstream of hardware manufacturing industry is still taking benefits of products and the performance of chips as priority, restricting the design of hardware secure countermeasures under a compromise to a finite expense of overheads. Consider the development trend of hardware industries and state-of-the-art researches of architecture designs, this dissertation proposes some new physical unclonable function (PUF) designs as countermeasures to side-channel attacks (SCA) and machine learning (ML) attacks simultaneously. Except for the joint consideration of hardware and software vulnerabilities, those designs also take efficiencies and overhead problems into consideration, making the new-style of PUF more possible to be merged into current chips as well as their design concepts. While the growth of artificial intelligence and machine-learning techniques dominate the researching trends of Internet of things (IoT) industry, some mainstream architectures of neural networks are implemented as hypothetical attacking model, whose results are used as references for further lifting the performance, the security level, and the efficiency in lateral studies. In addition, a study of implementation of neural networks on hardware designs is proposed, this realized the initial attempt to introduce AI techniques to the designs of voltage regulation (VR). All aforementioned works are demonstrated to be of robustness to threats with corresponding power attack tests or ML attack tests. Some conceptional models are proposed in the last of the dissertation as future plans so as to realize secure on-chip ML models and hardware countermeasures to hybrid threats

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

Secure and Unclonable Integrated Circuits

Semiconductor manufacturing is increasingly reliant in offshore foundries, which has raised concerns with counterfeiting, piracy, and unauthorized overproduction by the contract foundry. The recent shortage of semiconductors has aggravated such problems, with the electronic components market being flooded by recycled, remarked, or even out-of-spec, and defective parts. Moreover, modern internet connected applications require mechanisms that enable secure communication, which must be protected by security countermeasures to mitigate various types of attacks. In this thesis, we describe techniques to aid counterfeit prevention, and mitigate secret extraction attacks that exploit power consumption information. Counterfeit prevention requires simple and trustworthy identification. Physical unclonable functions (PUFs) harvest process variation to create a unique and unclonable digital fingerprint of an IC. However, learning attacks can model the PUF behavior, invalidating its unclonability claims. In this thesis, we research circuits and architectures to make PUFs more resilient to learning attacks. First, we propose the concept of non-monotonic response quantization, where responses not always encode the best performing circuit structure. Then, we explore the design space of PUF compositions, assessing the trade-off between stability and resilience to learning attacks. Finally, we introduce a lightweight key based challenge obfuscation technique that uses a chip unique secret to construct PUFs which are more resilient to learning attacks. Modern internet protocols demand message integrity, confidentiality, and (often) non-repudiation. Adding support for such mechanisms requires on-chip storage of a secret key. Even if the key is produced by a PUF, it will be subject to key extraction attacks that use power consumption information. Secure integrated circuits must address power analysis attacks with appropriate countermeasures. Traditional mitigation techniques have limited scope of protection, and impose several restrictions on how sensitive data must be manipulated. We demonstrate a bit-serial RISC-V microprocessor implementation with no plain-text data in the clear, where all values are protected using Boolean masking and differential domino logic. Software can run with little to no countermeasures, reducing code size and performance overheads. Our methodology is fully automated and can be applied to designs of arbitrary size or complexity. We also provide details on other key components such as clock randomizer, memory protection, and random number generator

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

Designing, Implementing, and Testing Hardware for Cybersecurity

Cybersecurity is one of the key issues facing the world today. With an ever-increasing number of devices connected across the internet, the need to secure all these different devices against potential attackers is an endless effort. This thesis is focussed on the most promising new developments in the hardware aspect of this battle for security. The first section of the thesis looks at what is the current state of the art when it comes to hardware security primitives, with a focus on random number generators and Physically Unclonable Functions (PUF). The strengths and weakness of the current implementations of these systems are analysed so that the areas which are most in need of improvement can be highlighted. The second major section of this thesis is looking to improve how random numbers are generated, which is essential for many current security systems. True random number generators have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified true random number generator that exclusively uses conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bit rate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time, multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bit rates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by an LSTM neural network. The third major section describes the development of a novel PUF concept, which offers a new approach to authentication, allowing low power devices to be included in existing networks without compromising overall security. The new PUF concept introduces time dependence to vastly increase the efficiency of entropy source usage, when compared with a traditional PUF. This new PUF also introduces a probability-based model which greatly reduces the required server memory for Challenge Response Pair (CRP) storage when large numbers of CRPs are used. The concept is verified experimentally on nano-scale CMOS technology as well as through simulation and a proof-of-concept circuit. These combined benefits bring the PUF concept much closer to being a viable solution for widespread cybersecurity applications

Stochastic Memory Devices for Security and Computing

With the widespread use of mobile computing and internet of things, secured communication and chip authentication have become extremely important. Hardware-based security concepts generally provide the best performance in terms of a good standard of security, low power consumption, and large-area density. In these concepts, the stochastic properties of nanoscale devices, such as the physical and geometrical variations of the process, are harnessed for true random number generators (TRNGs) and physical unclonable functions (PUFs). Emerging memory devices, such as resistive-switching memory (RRAM), phase-change memory (PCM), and spin-transfer torque magnetic memory (STT-MRAM), rely on a unique combination of physical mechanisms for transport and switching, thus appear to be an ideal source of entropy for TRNGs and PUFs. An overview of stochastic phenomena in memory devices and their use for developing security and computing primitives is provided. First, a broad classification of methods to generate true random numbers via the stochastic properties of nanoscale devices is presented. Then, practical implementations of stochastic TRNGs, such as hardware security and stochastic computing, are shown. Finally, future challenges to stochastic memory development are discussed