Browsing by Author "Ball, Arthur Hugues"
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- Analysis of Lightweight Cryptographic PrimitivesGeorge, Kiernan Brent (Virginia Tech, 2021-05-05)Internet-of-Things (IoT) devices have become increasingly popular in the last 10 years, yet also show an acceptance for lack of security due to hardware constraints. The range of sophistication in IoT devices varies substantially depending on the functionality required, so security options need to be flexible. Manufacturers typically either use no security, or lean towards the use of the Advanced Encryption Standard (AES) with a 128-bit key. AES-128 is suitable for the higher end of that IoT device range, but is costly enough in terms of memory, time, and energy consumption that some devices opt to use no security. Short development and a strong drive to market also contribute to a lack in security. Recent work in lightweight cryptography has analyzed the suitability of custom protocols using AES as a comparative baseline. AES outperforms most custom protocols when looking at security, but those analyses fail to take into account block size and future capabilities such as quantum computers. This thesis analyzes lightweight cryptographic primitives that would be suitable for use in IoT devices, helping fill a gap for "good enough" security within the size, weight, and power (SWaP) constraints common to IoT devices. The primitives have not undergone comprehensive cryptanalysis and this thesis attempts to provide a preliminary analysis of confidentiality. The first is a single-stage residue number system (RNS) pseudorandom number generator (PRNG) that was shown in previous publications to produce strong outputs when analyzed with statistical tests like the NIST RNG test suite and DIEHARD. However, through analysis, an intelligent multi-stage conditional probability attack based on the pigeonhole principle was devised to reverse engineer the initial state (key) of a single-stage RNS PRNG. The reverse engineering algorithm is presented and used against an IoT-caliber device to showcase the ability of an attacker to retrieve the initial state. Following, defenses based on intentional noise, time hopping, and code hopping are proposed. Further computation and memory analysis show the proposed defenses are simple in implementation, but increase complexity for an attacker to the point where reverse engineering the PRNG is likely no longer viable. The next primitive proposed is a block cipher combination technique based on Galois Extension Field multiplication. Using any PRNG to produce the pseudorandom stream, the block cipher combination technique generates a variable sized key matrix to encrypt plaintext. Electronic Codebook (ECB) and Cipher Feedback (CFB) modes of operation are discussed. Both system modes are implemented in MATLAB as well as on a Texas Instruments (TI) MSP430FR5994 microcontroller for hardware validation. A series of statistical tests are then run against the simulation results to analyze overall randomness, including NIST and the Law of the Iterated Logarithm; the system passes both. The implementation on hardware is compared against a stream cipher variation and AES-128. The block cipher proposed outperforms AES-128 in terms of computation time and consumption for small block sizes. While not as secure, the cryptosystem is more scalable to block sizes used in IoT devices.
- Applying Reservoir Computing for Driver Behavior Analysis and Traffic Flow Prediction in Intelligent Transportation SystemsSethi, Sanchit (Virginia Tech, 2024-06-05)In the realm of autonomous vehicles, ensuring safety through advanced anomaly detection is crucial. This thesis integrates Reservoir Computing with temporal-aware data analysis to enhance driver behavior assessment and traffic flow prediction. Our approach combines Reservoir Computing with autoencoder-based feature extraction to analyze driving metrics from vehicle sensors, capturing complex temporal patterns efficiently. Additionally, we extend our analysis to forecast traffic flow dynamics within road networks using the same framework. We evaluate our model using the PEMS-BAY and METRA-LA datasets, encompassing diverse traffic scenarios, along with a GPS dataset of 10,000 taxis, providing real-world driving dynamics. Through a support vector machine (SVM) algorithm, we categorize drivers based on their performance, offering insights for tailored anomaly detection strategies. This research advances anomaly detection for autonomous vehicles, promoting safer driving experiences and the evolution of vehicle safety technologies. By integrating Reservoir Computing with temporal-aware data analysis, this thesis contributes to both driver behavior assessment and traffic flow prediction, addressing critical aspects of autonomous vehicle systems.
- Modeling and Electrical Characterization of Ohmic Contacts on n-type GaNAyyagari, Sai Rama Usha (Virginia Tech, 2018-03-07)As the current requirements of power devices are moving towards high frequency, high efficiency and high-power density, Silicon-based devices are reaching its limits which are instigating the need to move towards new materials. Gallium Nitride (GaN) has the potential to meet the growing demands due to the wide band-gap nature which leads to various enhanced material properties like, higher operational temperature, smaller dimensions, faster operation and efficient performance. The metal contacts on semiconductors are essential as the interface properties affect the semiconductor performance and device operation. The low resistance ohmic contacts for n-GaN have been well established while most p-GaN devices have still high contact resistivity. Significant work has not been found that focuses on software-based modeling of the device to analyze the contact resistance and implement methods to reduce the contact resistivity. Understanding the interface physics in n-GaN devices using simulations can help in understanding the contacts on p-GaN and eventually reduce its metal contact resistivity. In this work, modeling of the metal-semiconductor interface along with the effect of a heavily doped layer under the metal contact is presented. The extent of reduction in contact resistivity due to different doping and thickness of n++ layer is presented with simulations. These results have been verified by the growth of device based on simulation results and reduction in contact resistivity has been observed. The effect of different TLM pattern along with different annealing conditions is presented in the work.
- Resistive Switching in Porous Low-k DielectricsAli, Rizwan (Virginia Tech, 2018-06-05)Integrating nanometer-sized pores into low-k ILD films is one of the approaches to lower the RC signal delay and thus help sustain the continued scaling of microelectronic devices. While increasing porosity of porous dielectrics lowers the dielectric constant (k), it also creates many reliability and implementation issues. One of the problems is the little understood metal ion diffusion and drift in porous media. Here, we present a rigorous simulation method of Cu diffusion based on Master equation with elementary jump probabilities within the contiguous dielectric film, along the pore boundary, from the dielectric matrix to the pore boundary, and from the pore boundary to the matrix material. In view of the diffusional jump distance being as large as 2 nm, the nano-pores being on a similar length scale, and the film thickness being only a few tens of nanometers, the conventional diffusion equation in differential equation form is grossly inadequate and elementary jump frequencies are required for a proper description of the Cu diffusion in porous dielectric. The present atomistic approach allows a consistent implementation of Cu ion drift in electric field by lowering and raising of the diffusion barriers along the field direction. This will help understand the behavior of Cu interconnects under thermal or electric stress at an atomistic level. Another approach to lower the increasing RC delays is to bring memory and logic closer by integrating memory in the BEOL. Resistive RAM is one such memory is not transistor based and thus, does not require a silicon substrate. Thus, it offers the possibility of integration directly into the back-end reducing memory to logic distance from 1000s of µm to a 10s of nm. This 3D integration also allows for increased density as well. However, one barrier in the implementation of RRAM in the back end is the use of expensive as well as non-BEOL native material in conventional Cu/TaOx/Pt resistive devices. In this thesis, we present our research about functionality of RRAM with porous low-k dielectrics (which are a candidate for CMOS ILD), and through the similar elementary jump simulations, discuss the impact of porosity in dielectrics on the functionality of RRAM. Lastly, we present a cheaper replacement for Pt as the counter electrode in RRAM and show that it functions as good as Pt. This work addresses following three areas: 1. Modeling of diffusion in porous dielectrics through elementary jump based simulation. The model is based on random walk theory of elementary particle jumps. Initially, qualitative simulations are conducted without actual parameters. It is shown that Cu diffusion in porous dielectrics decreases quasi-linearly with porosity. Furthermore, it is shown that morphology of the pores may have a greater effect on diffusivity compared to porosity. The simulations are then calibrated with parameters, and the result is shown to yield a similar diffusivity times as actual process time. 2. Modeling of Cu ions drift in porous dielectrics under electric stress. First, the model is explained, and then qualitative simulation results are presented for porous dielectrics with varied porosities and morphologies. 3. Research to find a suitable replacement for Pt as the counter electrode in RRAM devices. The research methodology is discussed and a much cheaper Rh is selected as the potential replacement for Pt. Successful functionality of Rh based resistive devices is presented.
- Wireless Information and Power Transfer Methods for IoT ApplicationsReed, Ryan Tyler (Virginia Tech, 2021-07-12)As Internet of Things (IoT) technology continues to become more commonplace, demand for self-sustainable and low-power networking schemes has increased. Future IoT devices will require a ubiquitous energy source and will need to be capable of low power communication. RF energy can be harvested through ambient or dedicated RF sources to satisfy this energy demand. In addition, these RF signals can be modified to convey information. This thesis surveys a variety of RF energy harvesting methods. A new low complexity energy harvesting system (circuit and antenna) is proposed. Low power communication schemes are examined, and low complexity and efficient transmitter designs are developed that utilize RF backscattering, harmonics, and intermodulation products. These communication schemes operate with minimal power consumption and can be powered solely from harvested RF energy. The RF energy harvester and RF-powered transmitters designs are validated through simulation, prototyping, and measurements. The results are compared to the performance of state-of-the-art devices described in the literature.