Subwavelength Engineering of Silicon Photonic Waveguides

The dissertation demonstrates subwavelength engineering of silicon photonic waveguides in the form of two different structures or avenues: (i) a novel ultra-low mode area v-groove waveguide to enhance light-matter interaction; and (ii) a nanoscale sidewall crystalline grating performed as physical unclonable function to achieve hardware and information security. With the advancement of modern technology and modern supply chain throughout the globe, silicon photonics is set to lead the global semiconductor foundries, thanks to its abundance in nature and a mature and well-established industry. Since, the silicon waveguide is the heart of silicon photonics, it can be considered as the core building block of modern integrated photonic systems. Subwavelength structuring of silicon waveguides shows immense promise in a variety of field of study, such as, tailoring electromagnetic near fields, enhancing light-matter interactions, engineering anisotropy and effective medium effects, modal and dispersion engineering, nanoscale sensitivity etc. In this work, we are going to exploit the boundary conditions of modern silicon photonics through subwavelength engineering by means of novel ultra-low mode area v-groove waveguide to answer long-lasting challenges, such as, fabrication of such sophisticated structure while ensuring efficient coupling of light between dissimilar modes. Moreover, physical unclonable function derived from our nanoscale sidewall crystalline gratings should give us a fast and reliable optical security solution with improved information density. This research should enable new avenues of subwavelength engineered silicon photonic waveguide and answer to many unsolved questions of silicon photonics foundries

A Physical Unclonable Function Based on Inter-Metal Layer Resistance Variations and an Evaluation of its Temperature and Voltage Stability

Keying material for encryption is stored as digital bistrings in non-volatile memory (NVM) on FPGAs and ASICs in current technologies. However, secrets stored this way are not secure against a determined adversary, who can use probing attacks to steal the secret. Physical Unclonable functions (PUFs) have emerged as an alternative. PUFs leverage random manufacturing variations as the source of entropy for generating random bitstrings, and incorporate an on-chip infrastructure for measuring and digitizing the corresponding variations in key electrical parameters, such as delay or voltage. PUFs are designed to reproduce a bitstring on demand and therefore eliminate the need for on-chip storage. In this dissertation, I propose a kind of PUF that measures resistance variations in inter-metal layers that define the power grid of the chip and evaluate its temperature and voltage stability. First, I introduce two implementations of a power grid-based PUF (PG-PUF). Then, I analyze the quality of bit strings generated without considering environmental variations from the PG-PUFs that leverage resistance variations in: 1) the power grid metal wires in 60 copies of a 90 nm chip and 2) in the power grid metal wires of 58 copies of a 65 nm chip. Next, I carry out a series of experiments in a set of 63 chips in IBM\u27s 90 nm technology at 9 TV corners, i.e., over all combination of 3 temperatures: -40oC, 25oC and 85oC and 3 voltages: nominal and +/-10% of the nominal supply voltage. The randomness, uniqueness and stability characteristics of bitstrings generated from PG-PUFs are evaluated. The stability of the PG-PUF and an on-chip voltage-to-digital (VDC) are also evaluated at 9 temperature-voltage corners. I introduce several techniques that have not been previously described, including a mechanism to eliminate voltage trends or \u27bias\u27 in the power grid voltage measurements, as well as a voltage threshold, Triple-Module-Redundancy (TMR) and majority voting scheme to identify and exclude unstable bits

Within-Die Delay Variation Measurement And Analysis For Emerging Technologies Using An Embedded Test Structure

Both random and systematic within-die process variations (PV) are growing more severe with shrinking geometries and increasing die size. Escalation in the variations in delay and power with reductions in feature size places higher demands on the accuracy of variation models. Their availability can be used to improve yield, and the corresponding profitability and product quality of the fabricated integrated circuits (ICs). Sources of within-die variations include optical source limitations, and layout-based systematic effects (pitch, line-width variability, and microscopic etch loading). Unfortunately, accurate models of within-die PVs are becoming more difficult to derive because of their increasingly sensitivity to design-context. Embedded test structures (ETS) continue to play an important role in the development of models of PVs and as a mechanism to improve correlations between hardware and models. Variations in path delays are increasing with scaling, and are increasingly affected by neighborhood\u27 interactions. In order to fully characterize within-die variations, delays must be measured in the context of actual core-logic macros. Doing so requires the use of an embedded test structure, as opposed to traditional scribe line test structures such as ring oscillators (RO). Accurate measurements of within-die variations can be used, e.g., to better tune models to actual hardware (model-to-hardware correlations). In this research project, I propose an embedded test structure called REBEL (Regional dELay BEhavior) that is designed to measure path delays in a minimally invasive fashion; and its architecture measures the path delays more accurately. Design for manufacture-ability (DFM) analysis is done on the on 90 nm ASIC chips and 28nm Zynq 7000 series FPGA boards. I present ASIC results on within-die path delay variations in a floating-point unit (FPU) fabricated in IBM\u27s 90 nm technology, with 5 pipeline stages, used as a test vehicle in chip experiments carried out at nine different temperature/voltage (TV) corners. Also experimental data has been analyzed for path delay variations in short vs long paths. FPGA results on within-die variation and die-to-die variations on Advanced Encryption System (AES) using single pipelined stage are also presented. Other analysis that have been performed on the calibrated path delays are Flip Flop propagation delays for both rising and falling edge (tpHL and tpLH), uncertainty analysis, path distribution analysis, short versus long path variations and mid-length path within-die variation. I also analyze the impact on delay when the chips are subjected to industrial-level temperature and voltage variations. From the experimental results, it has been established that the proposed REBEL provides capabilities similar to an off-chip logic analyzer, i.e., it is able to capture the temporal behavior of the signal over time, including any static and dynamic hazards that may occur on the tested path. The ASIC results further show that path delays are correlated to the launch-capture (LC) interval used to time them. Therefore, calibration as proposed in this work must be carried out in order to obtain an accurate analysis of within-die variations. Results on ASIC chips show that short paths can vary up to 35% on average, while long paths vary up to 20% at nominal temperature and voltage. A similar trend occurs for within-die variations of mid-length paths where magnitudes reduced to 20% and 5%, respectively. The magnitude of delay variations in both these analyses increase as temperature and voltage are changed to increase performance. The high level of within-die delay variations are undesirable from a design perspective, but they represent a rich source of entropy for applications that make use of \u27secrets\u27 such as authentication, hardware metering and encryption. Physical unclonable functions (PUFs) are a class of primitives that leverage within-die-variations as a means of generating random bit strings for these types of applications, including hardware security and trust. Zynq FPGAs Die-to-Die and within-die variation study shows that on average there is 5% of within-Die variation and the range of die-to-Die variation can go upto 3ns. The die-to-Die variations can be explored in much further detail to study the variations spatial dependance. Additionally, I also carried out research in the area data mining to cater for big data by focusing the work on decision tree classification (DTC) to speed-up the classification step in hardware implementation. For this purpose, I devised a pipelined architecture for the implementation of axis parallel binary decision tree classification for meeting up with the requirements of execution time and minimal resource usage in terms of area. The motivation for this work is that analyzing larger data-sets have created abundant opportunities for algorithmic and architectural developments, and data-mining innovations, thus creating a great demand for faster execution of these algorithms, leading towards improving execution time and resource utilization. Decision trees (DT) have since been implemented in software programs. Though, the software implementation of DTC is highly accurate, the execution times and the resource utilization still require improvement to meet the computational demands in the ever growing industry. On the other hand, hardware implementation of DT has not been thoroughly investigated or reported in detail. Therefore, I propose a hardware acceleration of pipelined architecture that incorporates the parallel approach in acquiring the data by having parallel engines working on different partitions of data independently. Also, each engine is processing the data in a pipelined fashion to utilize the resources more efficiently and reduce the time for processing all the data records/tuples. Experimental results show that our proposed hardware acceleration of classification algorithms has increased throughput, by reducing the number of clock cycles required to process the data and generate the results, and it requires minimal resources hence it is area efficient. This architecture also enables algorithms to scale with increasingly large and complex data sets. We developed the DTC algorithm in detail and explored techniques for adapting it to a hardware implementation successfully. This system is 3.5 times faster than the existing hardware implementation of classification.\u2

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

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

A Survey of hardware protection of design data for integrated circuits and intellectual properties

International audienceThis paper reviews the current situation regarding design protection in the microelectronics industry. Over the past ten years, the designers of integrated circuits and intellectual properties have faced increasing threats including counterfeiting, reverse-engineering and theft. This is now a critical issue for the microelectronics industry, mainly for fabless designers and intellectual properties designers. Coupled with increasing pressure to decrease the cost and increase the performance of integrated circuits, the design of a secure, efficient, lightweight protection scheme for design data is a serious challenge for the hardware security community. However, several published works propose different ways to protect design data including functional locking, hardware obfuscation, and IC/IP identification. This paper presents a survey of academic research on the protection of design data. It concludes with the need to design an efficient protection scheme based on several properties

Nano-intrinsic security primitives for internet of everything

With the advent of Internet-enabled electronic devices and mobile computer systems, maintaining data security is one of the most important challenges in modern civilization. The innovation of physically unclonable functions (PUFs) shows great potential for enabling low-cost low-power authentication, anti-counterfeiting and beyond on the semiconductor chips. This is because secrets in a PUF are hidden in the randomness of the physical properties of desirably identical devices, making it extremely difficult, if not impossible, to extract them. Hence, the basic idea of PUF is to take advantage of inevitable non-idealities in the physical domain to create a system that can provide an innovative way to secure device identities, sensitive information, and their communications. While the physical variation exists everywhere, various materials, systems, and technologies have been considered as the source of unpredictable physical device variation in large scales for generating security primitives. The purpose of this project is to develop emerging solid-state memory-based security primitives and examine their robustness as well as feasibility. Firstly, the author gives an extensive overview of PUFs. The rationality, classification, and application of PUF are discussed. To objectively compare the quality of PUFs, the author formulates important PUF properties and evaluation metrics. By reviewing previously proposed constructions ranging from conventional standard complementary metal-oxide-semiconductor (CMOS) components to emerging non-volatile memories, the quality of different PUFs classes are discussed and summarized. Through a comparative analysis, emerging non-volatile redox-based resistor memories (ReRAMs) have shown the potential as promising candidates for the next generation of low-cost, low-power, compact in size, and secure PUF. Next, the author presents novel approaches to build a PUF by utilizing concatenated two layers of ReRAM crossbar arrays. Upon concatenate two layers, the nonlinear structure is introduced, and this results in the improved uniformity and the avalanche characteristic of the proposed PUF. A group of cell readout method is employed, and it supports a massive pool of challenge-response pairs of the nonlinear ReRAM-based PUF. The non-linear PUF construction is experimentally assessed using the evaluation metrics, and the quality of randomness is verified using predictive analysis. Last but not least, random telegraph noise (RTN) is studied as a source of entropy for a true random number generation (TRNG). RTN is usually considered a disadvantageous feature in the conventional CMOS designs. However, in combination with appropriate readout scheme, RTN in ReRAM can be used as a novel technique to generate quality random numbers. The proposed differential readout-based design can maintain the quality of output by reducing the effect of the undesired noise from the whole system, while the controlling difficulty of the conventional readout method can be significantly reduced. This is advantageous as the differential readout circuit can embrace the resistance variation features of ReRAMs without extensive pre-calibration. The study in this thesis has the potential to enable the development of cost-efficient and lightweight security primitives that can be integrated into modern computer mobile systems and devices for providing a high level of security

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