Theses and Dissertations
Advisor
Chaudhary, Vini
Committee Member
Manias, Dimitrios
Committee Member
Perkins, Andy
Committee Member
Mittal, Sudip
Date of Degree
5-15-2026
Original embargo terms
Embargo 6 months
Document Type
Graduate Thesis - Open Access
Major
Cybersecurity & Operations
Degree Name
Master of Science (M.S.)
College
James Worth Bagley College of Engineering
Department
Department of Computer Science and Engineering
Abstract
Cloud-based access to quantum hardware has become the dominant model for executing quantum workloads in the Noisy Intermediate-Scale Quantum (NISQ) era. However, a lack of transparency in quantum cloud platforms raises security and trust concerns, including the inability of users to verify which quantum processor executed their submitted circuits. Existing methods require the execution of thousands of circuits, which is expensive and time-consuming. This thesis proposes a method to address the circuit validation issue by creating a lightweight, calibration-based, quantum device fingerprinting framework that enrolls quantum fingerprints without requiring circuit execution or additional measurement overhead. This XGBoost model, trained on a custom dataset of calibration data from six IBM quantum devices, achieves 99.03% accuracy in binary classification and 82.85% accuracy in a multi-class experiment. Unlike state-of-the-art methods that require hundreds to thousands of circuits to be measured for similar accuracy, this approach offers a more cost-effective solution.
Recommended Citation
Patterson, Wilson, "Fingerprinting noisy intermediate-scale quantum cloud devices" (2026). Theses and Dissertations. 6960.
https://scholarsjunction.msstate.edu/td/6960
