Threat Analysis, Countermeaures and Design Strategies for Secure Computation in Nanometer CMOS Regime

Advancements in CMOS technologies have led to an era of Internet Of Things (IOT), where the devices have the ability to communicate with each other apart from their computational power. As more and more sensitive data is processed by embedded devices, the trend towards lightweight and efficient cryptographic primitives has gained significant momentum. Achieving a perfect security in silicon is extremely difficult, as the traditional cryptographic implementations are vulnerable to various active and passive attacks. There is also a threat in the form of hardware Trojans inserted into the supply chain by the untrusted third-party manufacturers for economic incentives. Apart from the threats in various forms, some of the embedded security applications such as random number generators (RNGs) suffer from the impacts of process variations and noise in nanometer CMOS. Despite their disadvantages, the random and unique nature of process variations can be exploited for generating unique identifiers and can be of tremendous use in embedded security. In this dissertation, we explore techniques for precise fault-injection in cryptographic hardware based on voltage/temperature manipulation and hardware Trojan insertion. We demonstrate the effectiveness of these techniques by mounting fault attacks on state-of-the-art ciphers. Physically Unclonable Functions (PUFs) are novel cryptographic primitives for extracting secret keys from complex manufacturing variations in integrated circuits (ICs). We explore the vulnerabilities of some of the popular strong PUF architectures to modeling attacks using Machine Learning (ML) algorithms. The attacks use silicon data from a test chip manufactured in IBM 32nm silicon-on-insulator (SOI) technology. Attack results demonstrate that the majority of strong PUF architectures can be predicted to very high accuracies using limited training data. We also explore the techniques to exploit unreliable data from strong PUF architectures and effectively use them to improve the prediction accuracies of modeling attacks. Motivated by the vulnerabilities of existing PUF architectures, we present a novel modeling attack resistant PUF architecture based on non-linear computing elements. Post-silicon validation results are used to demonstrate the effectiveness of the non-linear PUF architecture against modeling and fault-injection attacks. Apart from the techniques to improve the security of PUF circuits, we also present novel solutions to improve the performance of PUF circuits from the perspectives of IC fabrication and system/protocol design. Finally, we present a statistical benchmark suite to evaluate PUFs in conceptualization phase and also to enable fine-grained security assessments for varying PUF parameters. Data compressibility analyses for validating the statistical benchmark suite are also presented

Roadmap on optical security

Postprint (author's final draft

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 Novel Physical Unclonable Function (PUF) Featuring 0.113 FJ/B for IOT Devices

A physically unclonable function (PUF) is useful for authentication purposes and is a function created for its inherent uniqueness and inability of adversaries to duplicate it. In this thesis, a PUF is designed, which is a combination of both digital and analog circuits. This PUF could be designed partially based on a semi-automated approach using custom-built P-cells. The PUF is implemented using novel digital circuits, which have been designed using basic digital gates with a minimal number of transistors. The proposed PUF is developed by the introduction of a layer of multiplexers, which is triggered by a novel SR-latch based model for driving the selection lines. For a higher bit stability, the SR latch is combined with four-way asynchronous circuits, which are a class of coincident flip-flops. The resulted PUF consumes very little power and is suitable for sensors and low power applications. The proposed design was implemented in using the Cadence virtuoso IC 5.1.4 and based on the 180nm TSMC transistor models. The energy consumption and area of the proposed PUF is shown to be equal to 0.1132 fJ/bit and 8.03, which is considerably lower than the state of the arts. The uniqueness and reliability of the proposed PUF are estimated to be 48.66% and 99.33%

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

DESIGN AUTOMATION FOR CARBON NANOTUBE CIRCUITS CONSIDERING PERFORMANCE AND SECURITY OPTIMIZATION

As prevailing copper interconnect technology advances to its fundamental physical limit, interconnect delay due to ever-increasing wire resistivity has greatly limited the circuit miniaturization. Carbon nanotube (CNT) interconnects have emerged as promising replacement materials for copper interconnects due to their superior conductivity. Buffer insertion for CNT interconnects is capable of improving circuit timing of signal nets with limited buffer deployment. However, due to the imperfection of fabricating long straight CNT, there exist significant unidimensional-spatially correlated variations on the critical CNT geometric parameters such as the diameter and density, which will affect the circuit performance. This dissertation develops a novel timing driven buffer insertion technique considering unidimensional correlations of variations of CNT. Although the fabrication variations of CNTs are not desired for the circuit designs targeting performance optimization and reliability, these inherent imperfections make them natural candidates for building highly secure physical unclonable function (PUF), which is an advanced hardware security technology. A novel CNT PUF design through leveraging Lorenz chaotic system is developed and we show that it is resistant to many machine learning modeling attacks. In summary, the studies in this dissertation demonstrate that CNT technology is highly promising for performance and security optimizations in advanced VLSI circuit design