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Quantum Machine Learning

Protecting Quantum Circuits Through Compiler-Resistant Obfuscation

arXiv
Authors: Pradyun Parayil, Amal Raj, Vivek Balachandran

Year

2025

Paper ID

36407

Status

Preprint

Abstract Read

~2 min

Abstract Words

113

Citations

N/A

Abstract

Quantum circuit obfuscation is becoming increasingly important to prevent theft and reverse engineering of quantum algorithms. As quantum computing advances, the need to protect the intellectual property contained in quantum circuits continues to grow. Existing methods often provide limited defense against structural and statistical analysis or introduce considerable overhead. In this paper, we propose a novel quantum obfuscation method that uses randomized U3 transformations to conceal circuit structure while preserving functionality. We implement and assess our approach on QASM circuits using Qiskit AER, achieving over 93% semantic accuracy with minimal runtime overhead. The method demonstrates strong resistance to reverse engineering and structural inference, making it a practical and effective approach for quantum software protection.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • Quantum circuit obfuscation is becoming increasingly important to prevent theft and reverse engineering of quantum algorithms.

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