Survey PaperMitigating Side-Channel Vulnerabilities in FPGA-Based Post-Quantum Cryptography: A Comprehensive Study
Abstract: The rise of quantum computing poses a significant threat to the security of classical cryptographic systems, making Post-Quantum Cryptography (PQC) essential for safeguarding data against quantum-based attacks. Field-Programmable Gate Arrays (FPGAs) are favored for implementing PQC algorithms due to their flexibility and reconfigurability. However, the complexity of these algorithms increases the vulnerability of FPGAs to side-channel attacks. Side-channel attacks allow attackers to extract sensitive information through physical characteristics like power consumption and timing variations. This survey comprehensively reviews how lattice-based PQC algorithms exacerbate these vulnerabilities, particularly CRYSTALS-Kyber and CRYSTALS-Dilithium. Although researchers have explored techniques to mitigate side-channel risks by modifying code to achieve uniform power consumption and execution times, complete uniformity remains challenging. As a result, there is an urgent need for more effective countermeasures, both in software and hardware design, to protect FPGA implementations from side-channel attacks.
Independent Research Study"Independent Research Study," Fall 2023. During the fall of my senior year of undergrad, I completed an independent research study with my Computer Engineering advisor, Dr. Hoe. This research paper presents a comprehensive exploration of quantum computing, focusing on the groundbreaking Shor’s algorithm and its profound implications for computational complexity and cryptography. Central to this study is the examination of key quantum principles such as phase kickback, modular arithmetic, and the Quantum Fourier Transform (QFT), which enable efficient solutions to problems like integer factorization—challenges that are computationally prohibitive for classical computers.
The paper begins by introducing phase kickback, a fundamental phenomenon in quantum operations, explaining its critical role in encoding quantum information through controlled unitary operations. The discussion then transitions to Shor’s algorithm, breaking down its components, from modular arithmetic and period-finding to the use of the QFT to extract periodicity from quantum states. Practical insights into the algorithm’s implementation on modern quantum hardware highlight challenges such as coherent noise, gate imperfections, and resource constraints. Quantum Machine Learning"Quantum Computing," Fall 2022. At the end of the semester, each student was tasked with a Quantum based research project. My partner and I chose Quantum Machine Learning and dissected Schuld’s 2021 paper about the implementation of a simple quantum machine learning classification circuit with a Titanic dataset. Kaggle has Titanic data sets that have been used for machine learning. These data sets consist of different variables, such as class, sex, age, number of siblings, number of parents, ticket number, ticket price, and cabin number. All of these variables play a factor in if someone died or survived the sinking, but in this case, only two variables will be compared, ticket price and cabin number. Schuld’s paper starts with the setup of the Titanic data set in order to be used in a quantum simulator. Once the data has been normalized onto a unit circle and then preprocessed into qubit states, the data can be sent through the simulator. The quantum circuit can be coded with NumPy to verify the outcomes of the data. The use of Numpy is straightforward, as the user can create the matrices
needed in the circuit and then be multiplied together to give the necessary output. |
Survey Paper December 2024
Study of Shor’s Algorithm and Quantum Challenges
Quantum Machine Learning Research Paper
Hadamard Application Presentation
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Junior Design: Rover“Inaugural Loyola Junior Design,” Fall 2022. This class is designed to help prepare juniors for their senior design capstone projects. Junior Design develops skills for integrating many technologies, including CAD, 3D printers, laser printers, motors (Servo and DC), Bluetooth devices, and H-bridge systems. Each group of five engineering juniors, consisting of mechanical, material, computer, and electrical engineers, was tasked with building a rover from the website howtomechatronics.com. Additionally, each group brainstormed and designed an attachment for the rover. Our group chose to design a lift that would attach to the front of the rover. The rover was Arduino based, so I gained hands-on experience with Arduino and its coding. Throughout the semester, each group gave three formal poster presentations leading to the final demonstration of our working rovers.
The inaugural Junior Design course was challenging and motivating. I spent nights and weekends in the lab, working alone and with my teammates to build and test the rover, ensuring that everything functioned correctly at each step. I genuinely enjoyed the design and redesign process and took advantage of the opportunity to learn domain specific skills from the other students on my team. Our team demonstrated the ability to flex between different leadership roles and found the most efficient ways to work productively together |
Junior Design Rover Group
Rover Video Presentation
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Quantum Simulator“Quantum Computing,” Spring 2023. Throughout the semester, student groups programmed a quantum computing simulator with Python. Each group included four students, consisting of computer engineers, computer science, and physics majors. The code comprised five main files: util, qubit, state, moment, gate, and circuit. The simulator would take the inputs of the zero and one kets and send them through an algorithm, such as Deutsch’s Algorithm, and compute the output. This project required significant collaboration, as each of us brought our individual strengths to the group. For example, the computer science major shared advanced Python concepts with the group, and the computer engineer and physics majors deconstructed the concepts learned in class so that each step could be translated into code. The program took us three months to create, and it can now successfully run different algorithms based on user inputs
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Quantum Computing Simulator Group
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