ENERGY-EFFICIENT AND SECURE HARDWARE FOR INTERNET OF THINGS (IoT) DEVICES

Internet of Things (IoT) is a network of devices that are connected through the Internet to exchange the data for intelligent applications. Though IoT devices provide several advantages to improve the quality of life, they also present challenges related to security. The security issues related to IoT devices include leakage of information through Differential Power Analysis (DPA) based side channel attacks, authentication, piracy, etc. DPA is a type of side-channel attack where the attacker monitors the power consumption of the device to guess the secret key stored in it. There are several countermeasures to overcome DPA attacks. However, most of the existing countermeasures consume high power which makes them not suitable to implement in power constraint devices. IoT devices are battery operated, hence it is important to investigate the methods to design energy-efficient and secure IoT devices not susceptible to DPA attacks. In this research, we have explored the usefulness of a novel computing platform called adiabatic logic, low-leakage FinFET devices and Magnetic Tunnel Junction (MTJ) Logic-in-Memory (LiM) architecture to design energy-efficient and DPA secure hardware. Further, we have also explored the usefulness of adiabatic logic in the design of energy-efficient and reliable Physically Unclonable Function (PUF) circuits to overcome the authentication and piracy issues in IoT devices. Adiabatic logic is a low-power circuit design technique to design energy-efficient hardware. Adiabatic logic has reduced dynamic switching energy loss due to the recycling of charge to the power clock. As the first contribution of this dissertation, we have proposed a novel DPA-resistant adiabatic logic family called Energy-Efficient Secure Positive Feedback Adiabatic Logic (EE-SPFAL). EE-SPFAL based circuits are energy-efficient compared to the conventional CMOS based design because of recycling the charge after every clock cycle. Further, EE-SPFAL based circuits consume uniform power irrespective of input data transition which makes them resilience against DPA attacks. Scaling of CMOS transistors have served the industry for more than 50 years in providing integrated circuits that are denser, and cheaper along with its high performance, and low power. However, scaling of the transistors leads to increase in leakage current. Increase in leakage current reduces the energy-efficiency of the computing circuits,and increases their vulnerability to DPA attack. Hence, it is important to investigate the crypto circuits in low leakage devices such as FinFET to make them energy-efficient and DPA resistant. In this dissertation, we have proposed a novel FinFET based Secure Adiabatic Logic (FinSAL) family. FinSAL based designs utilize the low-leakage FinFET device along with adiabatic logic principles to improve energy-efficiency along with its resistance against DPA attack. Recently, Magnetic Tunnel Junction (MTJ)/CMOS based Logic-in-Memory (LiM) circuits have been explored to design low-power non-volatile hardware. Some of the advantages of MTJ device include non-volatility, near-zero leakage power, high integration density and easy compatibility with CMOS devices. However, the differences in power consumption between the switching of MTJ devices increase the vulnerability of Differential Power Analysis (DPA) based side-channel attack. Further, the MTJ/CMOS hybrid logic circuits which require frequent switching of MTJs are not very energy-efficient due to the significant energy required to switch the MTJ devices. In the third contribution of this dissertation, we have investigated a novel approach of building cryptographic hardware in MTJ/CMOS circuits using Look-Up Table (LUT) based method where the data stored in MTJs are constant during the entire encryption/decryption operation. Currently, high supply voltage is required in both writing and sensing operations of hybrid MTJ/CMOS based LiM circuits which consumes a considerable amount of energy. In order to meet the power budget in low-power devices, it is important to investigate the novel design techniques to design ultra-low-power MTJ/CMOS circuits. In the fourth contribution of this dissertation, we have proposed a novel energy-efficient Secure MTJ/CMOS Logic (SMCL) family. The proposed SMCL logic family consumes uniform power irrespective of data transition in MTJ and more energy-efficient compared to the state-of-art MTJ/ CMOS designs by using charge sharing technique. The other important contribution of this dissertation is the design of reliable Physical Unclonable Function (PUF). Physically Unclonable Function (PUF) are circuits which are used to generate secret keys to avoid the piracy and device authentication problems. However, existing PUFs consume high power and they suffer from the problem of generating unreliable bits. This dissertation have addressed this issue in PUFs by designing a novel adiabatic logic based PUF. The time ramp voltages in adiabatic PUF is utilized to improve the reliability of the PUF along with its energy-efficiency. Reliability of the adiabatic logic based PUF proposed in this dissertation is tested through simulation based temperature variations and supply voltage variations

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

A CURRENT TO DIGITAL CONVERTER FOR POWER SIGNATURE GENERATION APPLICATIONS

The security of IoT devices is significantly increasing as a consequence of the widespread usage of the Internet of Things (IoT) in applications that include confidential data and implementation of important control decisions using those data. Because of their cheap cost and computational limitations, IoT devices confront significant obstacles in safeguarding. Among the variety of devised tactics analyzing power is one of the most potential strategies to address such challenges. However, due to the size, cost, and power consumption of power analysis devices, this strategy is not suited for many IoT applications. In this thesis, two techniques for collecting power signatures were proposed. A commercial 130nm CMOS technology is used to construct two circuits for each technique. For the purpose of determining how correctly the setups function, a considerable number of simulations are run under various conditions, and the results are assessed

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

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

Attacking and Defending Emerging Computer Systems Using The Memory Remanence Effect

In computer systems, manufacturing variances and hardware effects are typically abstracted away by the software layer. This dissertation explores how these effects, specifically memory remanence, can be used both as an attack vector and a tool to defend emerging computing systems. To achieve this, we show how time-keeping, anonymity, and authenticity can be affected by memory remanence. In terms of attacks, we explore the deanonymizing effect of approximate computing in the context of approximate memory in Probable Cause. We show how data passing through an approximate memory is watermarked with a device specific tag that points the attacker back to the device. In terms of defenses, we first present TARDIS: an approach to provide a notion of time for transiently powered embedded devices without requiring any hardware modification using remanence effect of SRAM. TARDIS allows these devices to keep a coarse-grained notion of time without the need for a running clock. Second, we propose data retention voltage of memory cells as a new type of physical unclonable function that allows for low-cost authentication and counterfeit resistance in computer systems.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136985/1/rahmati_1.pd

PUFs based on Coupled Oscillators Static Entropy

We live in a digital era, this led to a shift from traditional industry to a society focused on information and communication technologies. The amount of shared information is exponen- tially growing every year. Protecting all this shared information is keeping everyone’s privacy, is making sure the information is authentic, is keeping everyone safe. The solution for such problems is cryptography using hardware-based, System on Chip, SoC solutions such as Random Number Generators, RNGs, and Physical Unclonable Functions, PUFs. RNGs generate random keys from random processes that occurs inside the system. PUFs generate fixed random keys using random processes that originated in the fabrication process of the chip. The objective of this work is to study and compare a static entropy source based on coupled relaxation oscillators against a state-of-the-art architecture like the static entropy source based on ring oscillators, in advanced 130nm technology. The characteristic studied were, area, power consumption, entropy, resistance to temperature, and supply voltage varia- tions. Compared to the ring oscillator implementation, the static entropy source designed showed promising results as a static entropy source, however, it revealed poor results in terms of area, power consumption, and entropy. Such results mean, the coupled relaxation oscillator may not be good at generating random numbers, however, it may be good at keeping its state when under temperature and supply voltage variations.Vivemos numa era digital, o que levou a uma mudança da indústria tradicional para uma sociedade centrada sobre as tecnologias da informação e da comunicação. A quantidade de informação partilhada está a crescer exponencialmente todos os anos. Proteger toda esta in- formação partilhada é manter a privacidade de todos, é garantir que a informação é autêntica, está a manter todos seguros. A solução para tais problemas é a criptografia com base em soluções de hardware, Sys- tem on Chip, SoC tais como Geradores de Números Aleatórios, RNGs e Funções Físicas Inclo- náveis, PUFs. Os RNGs geram chaves aleatórias a partir de processos aleatórios que ocorrem no interior do sistema. Os PUFs geram chaves aleatórias fixas utilizando processos aleatórios que se originaram no processo de fabrico do chip. O principal objetivo deste trabalho é estudar e comparar uma fonte estática de entropia baseada em osciladores de relaxação acoplados contra uma arquitetura de estado de arte como a fonte estática de entropia baseada em osci- ladores de anel, em tecnologia avançada de 130nm. As características estudadas foram, a área, o consumo energia, a entropia, e a resistência à temperatura e variações de tensão de alimen- tação. Em comparação com a implementação do oscilador do anel, a fonte estática de entropia projetada mostrou resultados promissores como fonte estática de entropia, no entanto, reve- lou maus resultados em termos de área, consumo de energia e entropia. Estes resultados sig- nificam que o oscilador de relaxação acoplado pode não ser bom a gerar números aleatórios, no entanto, pode ser bom para manter o seu estado quando sujeito a variações de temperatura e tensão de alimentação

A low cost solution to authentication in passive RFID systems

Auto-ID Lab University of Adelaide (c) 2006 Copyright. The document attached has been archived with permission.This paper aims to propose a solution to address the issue of authentication to prevent counterfeiting in a low cost RFID based system based on using Physically Uncloneable Functions.Damith C. Ranasinghe, Daihyun Lim, Peter H. Cole and Srinivas Devada