On Improving Robustness of Hardware Security Primitives and Resistance to Reverse Engineering Attacks

The continued growth of information technology (IT) industry and proliferation of interconnected devices has aggravated the problem of ensuring security and necessitated the need for novel, robust solutions. Physically unclonable functions (PUFs) have emerged as promising secure hardware primitives that can utilize the disorder introduced during manufacturing process to generate unique keys. They can be utilized as \textit{lightweight} roots-of-trust for use in authentication and key generation systems. Unlike insecure non-volatile memory (NVM) based key storage systems, PUFs provide an advantage -- no party, including the manufacturer, should be able to replicate the physical disorder and thus, effectively clone the PUF. However, certain practical problems impeded the widespread deployment of PUFs. This dissertation addresses such problems of (i) reliability and (ii) unclonability. Also, obfuscation techniques have proven necessary to protect intellectual property in the presence of an untrusted supply chain and are needed to aid against counterfeiting. This dissertation explores techniques utilizing layout and logic-aware obfuscation. Collectively, we present secure and cost-effective solutions to address crucial hardware security problems

Energy Harvesting and Sensor Based Hardware Security Primitives for Cyber-Physical Systems

The last few decades have seen a large proliferation in the prevalence of cyber-physical systems. Although cyber-physical systems can offer numerous advantages to society, their large scale adoption does not come without risks. Internet of Things (IoT) devices can be considered a significant component within cyber-physical systems. They can provide network communication in addition to controlling the various sensors and actuators that exist within the larger cyber-physical system. The adoption of IoT features can also provide attackers with new potential avenues to access and exploit a system\u27s vulnerabilities. Previously, existing systems could more or less be considered a closed system with few potential points of access for attackers. Security was thus not typically a core consideration when these systems were originally designed. The cumulative effect is that these systems are now vulnerable to new security risks without having native security countermeasures that can easily address these vulnerabilities. Even just adding standard security features to these systems is itself not a simple task. The devices that make up these systems tend to have strict resource constraints in the form of power consumption and processing power. In this dissertation, we explore how security devices known as Physically Unclonable Functions (PUFs) could be used to address these concerns. PUFs are a class of circuits that are unique and unclonable due to inherent variations caused by the device manufacturing process. We can take advantage of these PUF properties by using the outputs of PUFs to generate secret keys or pseudonyms that are similarly unique and unclonable. Existing PUF designs are commonly based around transistor level variations in a special purpose integrated circuit (IC). Integrating these designs within a system would still require additional hardware along with system modification to interact with the device. We address these concerns by proposing a novel PUF design methodology for the creation of PUFs whose integration within these systems would minimize the cost of redesigning the system by reducing the need to add additional hardware. This goal is achieved by creating PUF designs from components that may already exist within these systems. A PUF designed from existing components creates the possibility of adding a PUF (and thus security features) to the system without actually adding any additional hardware. This could allow PUFs to become a more attractive security option for integration with resource constrained devices. Our proposed approach specifically targets sensors and energy harvesting devices since they can provide core functions within cyber-physical systems such as power generation and sensing capabilities. These components are known to exhibit variations due to the manufacturing process and could thus be utilized to design a PUF. Our first contribution is the proposal of a novel PUF design methodology based on using components which are already commonly found within cyber-physical systems. The proposed methodology uses eight sensors or energy harvesting devices along with a microcontroller. It is unlikely that single type of sensor or energy harvester will exist in all possible cyber-physical systems. Therefore, it is important to create a range of designs in order to reach a greater portion of cyber-physical systems. The second contribution of this work is the design of a PUF based on piezo sensors. Our third contribution is the design of a PUF that utilizes thermistor temperature sensors. The fourth contribution of this work is a proposed solar cell based PUF design. Furthermore, as a fifth contribution of this dissertation we evaluate a selection of common solar cell materials to establish which type of solar cell would be best suited to the creation of a PUF based on the operating conditions. The viability of the proposed designs is evaluated through testing in terms of reliability and uniformity. In addition, Monte Carlo simulations are performed to evaluate the uniqueness property of the designs. For our final contribution we illustrate the security benefits that can be achieved through the adoption of PUFs by cyber-physical systems. For this purpose we chose to highlight vehicles since they are a very popular example of a cyber-physical system and they face unique security challenges which are not readily solvable by standard solutions. Our contribution is the proposal of a novel controller area network (CAN) security framework that is based on PUFs. The framework does not require any changes to the underlying CAN protocol and also minimizes the amount of additional message passing overhead needed for its operation. The proposed framework is a good example of how the cost associated with implementing such a framework could be further reduced through the adoption of our proposed PUF designs. The end result is a method which could introduce security to an inherently insecure system while also making its integration as seamless as possible by attempting to minimize the need for additional hardware

A Modern Primer on Processing in Memory

Modern computing systems are overwhelmingly designed to move data to computation. This design choice goes directly against at least three key trends in computing that cause performance, scalability and energy bottlenecks: (1) data access is a key bottleneck as many important applications are increasingly data-intensive, and memory bandwidth and energy do not scale well, (2) energy consumption is a key limiter in almost all computing platforms, especially server and mobile systems, (3) data movement, especially off-chip to on-chip, is very expensive in terms of bandwidth, energy and latency, much more so than computation. These trends are especially severely-felt in the data-intensive server and energy-constrained mobile systems of today. At the same time, conventional memory technology is facing many technology scaling challenges in terms of reliability, energy, and performance. As a result, memory system architects are open to organizing memory in different ways and making it more intelligent, at the expense of higher cost. The emergence of 3D-stacked memory plus logic, the adoption of error correcting codes inside the latest DRAM chips, proliferation of different main memory standards and chips, specialized for different purposes (e.g., graphics, low-power, high bandwidth, low latency), and the necessity of designing new solutions to serious reliability and security issues, such as the RowHammer phenomenon, are an evidence of this trend. This chapter discusses recent research that aims to practically enable computation close to data, an approach we call processing-in-memory (PIM). PIM places computation mechanisms in or near where the data is stored (i.e., inside the memory chips, in the logic layer of 3D-stacked memory, or in the memory controllers), so that data movement between the computation units and memory is reduced or eliminated.Comment: arXiv admin note: substantial text overlap with arXiv:1903.0398

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

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

Cyber Security and Critical Infrastructures 2nd Volume

The second volume of the book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles, including an editorial that explains the current challenges, innovative solutions and real-world experiences that include critical infrastructure and 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within