Towards Fine-Grained Isolation Mechanisms for Intraprocess Isolation

Memory safety has long been a significant challenge in computer software security. In this thesis, we propose a set of methods to mitigate memory safety issues. Our approach allows for isolation of different functions and modules within an application at the granularity of individual functions, thereby preventing the spread of memory safety issues between these modules. With our thread-safe security monitor, developers can specify untrusted code and data requiring extra protection, thereby restricting access to sensitive information in two key ways. The first, called a sandbox, isolates error-prone components, such as those used for computation, protocol state machines, and parsers. The second, called a safebox, protects sensitive data or security-critical elements, including privilege flags, access tokens, and ACLs. This model enhances data protection and supports the incremental isolation of critical parts at minimal cost. We introduce an innovative combination of memory safety with contextual re- sources, allowing the allocation of isolation contexts for temporarily created resources. For instance, this enables the isolation of communication contents between connec- tions from different users, with sharing permitted only through securely isolated mod- ules. A typical example is a chat server where each client has its own context for handling user connections and encryption keys, preventing attackers from accessing other users’ information. The received data is shared among receiving users through a shared memory within a safe module which include sufficiently small TCB code (containing only the minimal code required for memory copying). Finally, develop- ers can set additional system resource policies for these contexts, thus limiting their access to file systems, networks, and other resources. By utilizing alias mapping, we map the same physical memory to multiple vir- tual memory addresses, allowing different modules to share data structures without frequent copying. We embed this alias into the higher bits of the virtual address, which enables efficient address translation across domains with minimal overhead and facilitates the seamless use of shared memory across function calls. We simplify the process by allowing developers to express intentions rather than operations through code annotations, improving maintainability. This information can coexist with regular software code and be dynamically enabled or disabled through our tools, optimizing the use of limited hardware resources while balancing security and performance. Our system demonstrated 95% compatibility in LTP testing, indicating its ca- pability to support most applications developed for the Linux platform, including those that utilize signals and multithreading, without requiring additional porting. We conducted several micro-benchmarks for the implementation mechanisms our sys- tem relies on, better illustrating the system’s overhead sources and providing clearer guidance for users. We implemented module isolation in real applications like NGINX and Redis and created separate isolation contexts for user connections. These evaluations demon- strate that our system can be easily and progressively applied in practical software. Our overhead for individual module isolation ranged from 3% to 10%. When isola- tion was performed on both dimensions simultaneously, our overhead reached 10% to 40

Beyond Dollars and Cents: Exploring Budgeting, Saving, and Financial Security in the Houston Area

This study explores Harris County residents’ financial security, looking at their budgeting and saving practices, barriers people face to budgeting and saving, and how these practices relate to someone being able to withstand economic shocks

A kinetic Monte Carlo simulation of solid-electrolyte interphase formation and dendrite growth during electroplating

The formation of 3D structures such as dendrite, filament, and moss during electroplating is an obstacle to the development of a number of battery systems vital to a sustainable future, particularly lithium metal batteries. The morphological evolution of lithium metal electrode is strongly affected by the presence of passivating species formed by electrolyte decomposition, known as solid-electrolyte interphase (SEI). A 2D kinetic Monte Carlo (kMC) algorithm on a hexagonal grid was developed to account for the competing effects of deposition, diffusion, and surface passivation, providing an elementary understanding of electrodeposition systems with passivation. Growth from flat electrode and from hemispherical nucleus were both investigated. Morphological information and shape statistics were found to be strongly controlled by both SEI initiation time and current density, and a phase map was constructed over both parameters to demonstrate the distribution of results. Spherical deposits formed at high passivation time and high flux, filaments and whiskers at low flux and high passivation time, and dendrites and mosses at high flux and low passivation time. SEI formation is also observed to exacerbate nascent diffusion instabilities on pristine electrode. In the limit of no cross-SEI diffusion, we obtain a scaling relation of filament lengthscale as flux^(0.35) t_pass^(2.17). When cross-SEI diffusion was considered, a contrast is observed between low and high flux regimes: traditionally, thickness decreases with current, but at high fluxes after SEI cracking, we observe that growth from a single active tip can sustain larger thicknesses with larger flux, shedding light on an SEI-free ultrahigh flux regime. These findings provide foundational yet novel understanding of complex SEI phenomena, potentially streamlining the design of next-generation batteries

The Gentrification Balancing Act: Exploring the Nexus of Stigma, Gentrification, and Media Discourse in Third Ward

Houston’s Third Ward is a historically Black neighborhood that has been undergoing gentrification for the past few decades. As a stigmatized place, Third Ward has been represented negatively in the media in prior decades. Now that the neighborhood is experiencing increased investment and development, what does that mean for its stigmatized reputation? As a neighborhood gentrifies and its demographic composition changes, neighborhood discourse changes to reflect a new neighborhood identity. The objective of this study is to understand the association of discourse change and neighborhood demographic change in Third Ward, uncovering how media discourse is involved in this process. Using structural topic modeling, I analyzed discourse changes in Houston Chronicle articles that mention Third Ward between 1985 and 2024. I find that most of the changes in discourse occur before gentrification. Further, discourse change does not align with neighborhood demographic change in expected ways. This study considers the role that discourse plays in how neighborhoods are both symbolically and physically constructed

Leveraging Multipath to Increase Radar Field-of-View and Sensing Performance

Radars are an indispensable sensing modality for autonomous navigation, vehicular networking and beyond, with features complementary to visible light sensing systems. Traditional radar signal processing estimates the range and radial velocity of objects in direct line-of-sight to the radar, i.e., objects directly illuminated by the radar that scatter the illumination back to the radar. However, line-of-sight signal processing limits radar performance in three ways. First, in radar systems with highly directional signal transmissions, e.g., those in the millimeter-wave and terahertz frequency bands, line-of-sight processing limits the field-of-view over which objects can be detected/sensed. Second, real-world signal propagation is rarely limited to line-of-sight propagation, and signals undergo significant multipath due to secondary reflections in the environment. Line-of-sight processing in presence of multipath results in the formation of false targets, a.k.a. ``ghosts,'' at physically incorrect locations, degrading accurate target detection and localization capabilities. Third, line-of-sight Doppler processing prevents radars from estimating the tangential velocities of moving objects, making it challenging to distinguish between objects that are stationary versus those that are moving tangentially to the radar. This thesis tackles all three limitations by rethinking the role of multipath in radar signal processing. The three parts of this thesis demonstrate how the three limitations can be overcome by treating multipath as an opportunity to leverage - by explicitly incorporating multipath into radar signal processing - rather than as a nuisance. The first part of this thesis theoretically demonstrates that leveraging multipath for radar imaging can improve radar resolution when multipath provides new ``looks'' of the imaging scene beyond those provided by line-of-sight, effectively forming a multi-``look'' synthetic aperture without requiring any physical aperture extension. The second and third parts of this thesis translate this theoretical idea into practice. The second part of this thesis utilizes the additional ``looks" provided by multipath to sense beyond-field-of-view objects that are imperceptible with line-of-sight processing, e.g., objects behind the radar or around-corners, without having to contend with the problem of multipath ``ghosts''. The final part of this thesis in turn uses multipath from static features in the environment (building pillars, walls, etc.), that may be known a-priori or estimated via beyond-field-of-view processing, to estimate both the tangential and radial velocities of line-of-sight moving objects. Overall, this thesis advocates for novel modeling and signal processing approaches to improve and unlock new sensing capabilities with existing radar systems. The methods proposed in this thesis are implementation-agnostic and are compatible with existing radar sensing and communication pipelines across different waveform choices and frequency bands. Hence, the results presented in this thesis are applicable to multiple use-cases, such as autonomous navigation, vehicular networking, emergency services, spatial computing, joint radar sensing and cellular communication, etc

Structure and Dilatational Response of Asphaltenes with Varying Solvent Quality

Defined by their solubility class, asphaltenes represent the most polar, aromatic, and heaviest fraction of crude oil. They strongly adsorb at oil-water interfaces, forming viscoelastic films that confer solid-like mechanical properties that stabilize crude oil emulsions. It is suggested that asphaltenes form the most stable crude oil emulsions close to the onset point of precipitation, in which soluble and insoluble asphaltene nanoaggregates are in solution. The formation of these emulsions leads to undesired flow assurance problems for the oil and gas industry that require demulsification to prevent operational challenges and costs. Given the heterogeneity in chemical composition, structure, and molecular weight of natural asphaltenes, it remains challenging to identify how their aggregation, precipitation, and diffusion behavior at oil-water interfaces promote stability. We use small-angle X-ray scattering (SAXS) and the oscillating pendant drop method to address this challenge and investigate the structure, aggregation behavior, and the dilatational rheology of asphaltenes and asphaltene-model molecule violanthrone-79 (VO-79) with decreasing solvent quality. We observed that the radius of gyration (Rg) is independent of solvent quality before the onset point of precipitation and decreases as solvent quality decreases. In addition, our results show that the complex dilatational modulus of soluble asphaltene nanoaggregates depends on the solvent quality and increases with aging. On the contrary, the interfacial dilatational response of VO-79 remains relatively constant with increasing aging and decreasing solvent quality. We hypothesize that soluble asphaltene nanoaggregates may be re-arranging at the oil-water interface due to their dispersed nature, thus influencing their packing and enhancing the mechanical proper- ties of the asphaltene-stabilized interfacial film, thereby promoting emulsion stability. The direct connection between structure and the dilatational response of oil-water interfaces stabilized by soluble asphaltenes is essential for understanding their interfacial properties and their role in the emulsification process near the onset point of precipitation. Understanding the relationship between the structural and interfacial features of soluble asphaltenes provides insights into developing effective demulsification strategies to prevent flow assurance issues associated with asphaltene-stabilized crude oil emulsions. Additionally, this work demonstrates feasibility in emulsion-based industrial applications

Employing ML Methods on Digitized FOIA Requests for Improved Discoverability and Policy Research

Born-digital records pose challenges for digital preservation due to their unstructured formats and noncompliance with accessibility standards. This project introduces a modular, open-source workflow to batch process large, mixed media PDFs—many obtained through FOIA requests—by leveraging OCR, AI, and named-entity recognition. Built for the White House Scientists Archive, this system enhances discoverability and usability of digitized records across administrations and supports metadata extraction at scale. Key tools include Mistral AI for OCR, Apache Tika for entity recognition, and a finet uned Mistral model for metadata generation

Advancing Biological Wastewater Treatment Resilience in Extreme Wet Weather Events

Wet weather events such as hurricanes, tropical storms and heavy precipitation are increasing in frequency and duration because of climate change. These events can overwhelm critical infrastructure such as Waste Resource Recovery Facilities (WRRFs), due to heavy flows and/or loads, also known as hydraulic overloading. Conventional WRRFs, which are predominantly suspended growth systems, are not well equipped to manage hydraulic overloading and may discharge partially treated or untreated wastewater into rivers, lakes, and other receiving water bodies. The high influx of influent can additionally lead to washout of the suspended biomass responsible for biological treatment in WRRFs. Biomass washout can disproportionally impact slow-growing microbial populations (e.g., nitrifiers) and thus result in a prolonged impact on nitrification and nitrogen removal processes. Biofilm-based attached growth treatment systems, such as moving bed bioreactor (MBBR) and membrane aerated bioreactor (MABR), have been proposed as a technology with the potential to improve the resiliency of WRRFs to wet weather events, by preventing biomass washout and protecting slow growing nitrifiers. This dissertation presents advancements in our understanding of how wet weather affects the resilience of biofilm-based wastewater treatment systems. The first objective of this research was to evaluate the impact hydraulic overloading due to wet weather on the immediate system function, nitrifier community composition and resilience of biofilm-based wastewater treatment systems. The next objective was to assess how wet weather disturbances will affect the biofilm system’s function, both in the long term and under real conditions. Given the potential benefits of biofilm-based wastewater treatment systems in maintaining function under wet weather events, finally, a community-wide resiliency analysis was conducted for historic and future wet weather scenarios. The impact of wet weather events on the functional and microbial community resilience of biofilm-based wastewater treatment system was evaluated with replicate bench-scale MBBRs were challenged with three different wet weather disturbances. Results showed that the nitrifier community and biofilm system’s function, in terms of ammonia-N and soluble organic carbon removal, were resilient to the wet weather disturbances as they recovered to the baseline levels post disturbance within hours. This work demonstrated that hydraulic overloading and starvation disturbances during wet weather events do not negatively impact the treatment systems’ function, microbial community structure and nitrifier community composition. Next, the nitrification efficiency and nitrifier community were evaluated using a pilot-scale MABR, installed at a City of Houston WRRF, Houston, USA, with real influent wastewater. The pilot-scale MABR system exhibited increased nitrification efficiency and an increase in nitrifier gene abundance one month post high flow event. A biofilm detachment strategy using periodic hydraulic overloading was thus proposed to boost the efficiency of ammonia-N removal in a MABR systems struggling with nitrification. Compared to the existing air scouring procedures, this liquid scouring method was demonstrated to also require less energy. Using the City of Houston as a case study, the performance and resilience of nine individual Houston WRRFs were analyzed for historic and future wet weather scenario to determine their impact on the community-wide resilience of the city. An outcome of this research was the opportunity to allow decision-makers to make strategic investments in WRRF infrastructure upgrades using biofilm systems and navigate tradeoffs with respect to resiliency and life cycle costs like capital investment and operating cost. Taken together, the results from the bench-scale, pilot-scale and community-scale studies of biofilm-based wastewater treatment systems advance the application of biofilm systems to improve the resilience of WRRFs to wet weather events

Lightweight Physical-Layer Security Primitives for 5G-and-Beyond Wireless Communications

The development of 5G-and-beyond wireless communication represents a major transition toward faster, more intelligent, and more flexible connectivity. Compared with previous generations, 5G-and-beyond systems are designed not only for higher data rates and larger capacity, but also for lower latency, enhanced intelligence, and broader applicability. These capabilities enable a wide range of mission-critical applications, such as immersive AR/VR, intelligent transportation, remote robotic surgery, and drone-assisted communication, where communication quality is tightly coupled with safety, efficiency, or privacy. However, the open nature of wireless propagation also introduces significant security concerns. In particular, as wireless transceivers become more mobile, autonomous, and distributed, it becomes increasingly difficult to verify their identity and prevent eavesdropping. These concerns raise new requirements for the transmitter (TX), which must be able to identify itself as a legitimate source and prevent sensitive information from leaking to unintended receivers. Traditionally, wireless security is achieved through digital cryptography. Although effective in many scenarios, cryptographic methods face four limitations when applied to future systems: (1) the added power and latency overhead becomes problematic for real-time bit-wise encryption, (2) key management becomes complex and power-hungry, and (3) physical signal leakage itself is not protected by encryption. To address these issues, physical-layer security (PLS) has gained increasing attention. By embedding security directly into the physical behavior of the TX, such as frequency, phase, amplitude, or time, PLS enables protection without relying on high-level cryptographic protocols. These techniques can be implemented with minimal latency, power, and area overhead, making them suitable for 5G-and-beyond systems where both performance and security are critical. This thesis focuses on low-overhead, TX-based physical-layer security techniques that address two major security requirements: (1) identification of TX to the receiver, and (2) prevention of wireless eavesdropping. Three system-level designs are proposed, each implemented with custom application-specific integrated circuit (ASIC) TXs and modules, and demonstrated through measurement. The first TX design addresses the identification problem. We propose a physical-layer identification TX that incorporates a digital physically unclonable function (PUF) to control its spectral regrowth. This creates a unique RF fingerprint (RFF) for each TX, beyond what is achievable with intrinsic process variation alone. A 2.4-GHz prototype is implemented in GlobalFoundries 45-nm CMOS SOI process with 4.7 dBm output power and 36% efficiency. Measurement results show significant improvement in RFF stability, uniqueness, and dynamic range compared to prior work. On top of it, we further enhance the identification performance with feature extraction and identification model. We develop a lightweight neural network that extracts PSD features from TX signals and performs device identification. The model is optimized for low-power implementation and works seamlessly with the proposed hardware. In measurement, 240 devices are identified with over 99% accuracy, and 40 devices at unseen distance achieve over 95%, demonstrating strong generalization and robustness under various conditions. The second TX design focuses on preventing sidelobe eavesdropping. We present a mm-Wave antenna subset modulation (ASM) TX operating at 28 GHz. By randomly selecting antenna subsets at the symbol rate, the transmitted I/Q symbols are scrambled outside the main direction, preventing eavesdropping without degrading performance in the desired direction. The ASIC is integrated with on-board antennas and includes a high-speed on-chip true random number generator (TRNG) for secure and unpredictable antenna selection. The system supports 1.2-Gb/s 64-QAM communication with ±2° information beamwidth and maintains high EVM performance. This work highlights the great potential and practicality of integrating ASM technology into future radios. In summary, this thesis proposes and demonstrates three low-overhead PLS techniques at the transmitter level, targeting future communication systems with tight constraints on power, latency, and security. These methods provide a practical and efficient way to enhance wireless security without relying on complicated cryptographic operations, and can serve as a complementary layer of protection in 5G-and-beyond wireless networks