Quantum circuit obfuscation is becoming increasingly impor-tant 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 struc-tural inference, making it a practical and effective approach for quantum software protection.
Quantum circuit obfuscation is becoming increasingly impor-tant 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 struc-tural inference, making it a practical and effective approach for quantum software protection.
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.
The success of quantum circuits in providing reliable outcomes for a given problem depends on the gate count and depth in near-term noisy quantum computers. Quantum circuit compilers that decompose high-level gates to native gates of the hardware and optimize the circuit play a key role in quantum computing. However, the quality and time complexity of the optimization process can vary significantly especially for practically relevant large-scale quantum circuits. As a result, third-party (often less-trusted/untrusted) compilers have emerged, claiming to provide better and faster optimization of complex quantum circuits than so-called trusted compilers. However, untrusted compilers can pose severe security risks, such as the theft of sensitive intellectual property (IP) embedded within the quantum circuit. We propose an obfuscation technique for quantum circuits using randomized reversible gates to protect them from such attacks during compilation. The idea is to insert a small random circuit into the original circuit and send it to the untrusted compiler. Since the circuit function is corrupted, the adversary may get incorrect IP. However, the user may also get incorrect output post-compilation. To circumvent this issue, we concatenate the inverse of the random circuit in the compiled circuit to recover the original functionality. We demonstrate the practicality of our method by conducting exhaustive experiments on a set of benchmark circuits and measuring the quality of obfuscation by calculating the Total Variation Distance (TVD) metric. Our method achieves TVD of up to 1.92 and performs at least 2X better than a previously reported obfuscation method. We also propose a novel adversarial reverse engineering (RE) approach and show that the proposed obfuscation is resilient against RE attacks. The proposed technique introduces minimal degradation in fidelity (~1% to ~3% on average).
Abstract The success of quantum circuits in providing reliable outcomes for a given problem depends on the gate count and depth in near-term noisy quantum computers. A circuit (that implements a given function) with a low gate count and short depth is more likely to give a correct solution than the circuit variant with a higher gate count and depth. As such, quantum circuit compilers that decompose high-level gates to native gates of the hardware and optimize the circuit play a key role in quantum computing. However, the quality and time complexity of the optimization process can vary significantly especially for practically relevant large-scale quantum circuits. As a result, third-party (often less-trusted/untrusted/unreliable) compilers have emerged, claiming to provide better and faster optimization of complex quantum circuits than so-called trusted compilers. However, untrusted compilers, with their varying adversarial motives ranging from semi-honest to malicious can pose severe security risks such as the theft of sensitive intellectual property (IP) embedded within the quantum circuit. We propose an obfuscation technique for quantum circuits using randomized reversible gates to protect them from such attacks during compilation. The idea is to insert a small random circuit into the original circuit and send it to the untrusted compiler. Since the circuit function is corrupted, the adversary (i.e., an untrusted compiler) may get incorrect IP. However, the user may also get incorrect output post-compilation (even though highly optimized). To circumvent this issue, we concatenate the inverse of the random circuit in the compiled circuit to recover the original functionality. We demonstrate the practicality of our method by conducting exhaustive experiments on a set of benchmark circuits and measuring the quality of obfuscation by calculating the Total Variation Distance (TVD) and Degree of Functional Corruption (DFC) metrics. Our method achieves TVD of up to 1.92, indicating substantial functional corruption, and performs at least 2x better than a previously reported obfuscation method. We also attained a DFC as low as -0.75, approaching the -1 score that represents maximal functional corruption, further ensuring the robustness of our proposed method against IP theft. We also propose a novel adversarial reverse engineering (RE) approach to extract the IP and show that the proposed obfuscation is resilient against RE attacks. The proposed technique introduces minimal degradation in fidelity ( ~ 1% to ~ 3% on average).
Quantum compilers play a crucial role in quantum computing by converting these algorithmic quantum circuits into forms compatible with specific quantum computer hardware. However, untrusted quantum compilers present considerable risks, including the potential theft of quantum circuit intellectual property (IP) and compromise of the functionality (e.g. Trojan insertion). Quantum circuit obfuscation techniques protect quantum IP by transforming a quantum circuit into a key-dependent version before compilation and restoring the compiled circuit's functionality with the correct key. This prevents the untrusted compiler from knowing the circuit's original functionality. Existing quantum circuit obfuscation techniques focus on inserting key qubits to control key gates. One added key gate can represent at most one Boolean key bit. In this paper, we propose OPAQUE, a phase-based quantum circuit obfuscation approach where we use the angle of rotation gates as the secret keys. The rotation angle is a continuous value, which makes it possible to represent multiple key bits. Moreover, phase gates are usually implemented as virtual gates in quantum hardware, diminishing their cost and impact on accuracy.
The developments in quantum computing hardware and software are focused on boosting the scalability and robustness of quantum systems. With near-term quantum computers poised to accelerate specific computational tasks, ensuring their security has become a pressing priority. Recent efforts have proposed practical solutions to ensure data confidentiality in quantum computers accessed through the cloud, particularly in the presence of untrusted quantum cloud providers by leveraging trusted hardware that enables quantum circuit obfuscation. However, these solutions overlook the detailed structural information of the quantum algorithms, which may limit the effectiveness of the obfuscation methods. In this paper, we investigate the structural constraints of quantum algorithms executed across different quantum architectures. Based on this analysis, we develop a Machine Learning (ML)-based classifier that reveals the underlying quantum algorithm of the obfuscated physical quantum circuit. We also propose a pre-processing phase to minimize the obfuscation's impact on the classifier accuracy. We evaluate our proposed ML-based classification model on different obfuscated physical quantum circuits, which are transpiled to support IBM quantum hardware. Our analysis shows the vulnerability of existing obfuscation methods to reverse engineering attacks, which can potentially expose sensitive information about quantum circuits.
Program obfuscation aims to conceal a computer program's internal structure while preserving its functionality. A central open problem is whether an obfuscation scheme for arbitrary quantum circuits exists. Despite several efforts toward this goal, prior works have succeeded only in obfuscating quantum circuits that implement either pseudo-deterministic functions or unitary transformations. Although unitary transformations already include a broad class of quantum computations, many important quantum tasks, such as state preparation, quantum sampling, and quantum error correction, go beyond unitaries and are described by general completely positive trace-preserving (CPTP) maps.
In this work, we construct the first quantum ideal obfuscation scheme for arbitrary quantum circuits that support quantum inputs and outputs in the classical oracle model assuming post-quantum one-way functions, thereby resolving an open problem raised in Bartusek et al. (STOC 2023), Bartusek, Brakerski, and Vaikuntanathan (STOC 2024), and Huang and Tang (FOCS 2025). At the core of our construction lies a novel primitive that we introduce, called the subspace-preserving strong pseudorandom unitary (spsPRU). An spsPRU is a family of efficient unitaries that fix every vector in a given linear subspace S, while acting as a Haar random unitary on its orthogonal complement S⊥ under both forward and inverse oracle queries. Furthermore, by instantiating the classical oracle model with the ideal obfuscation scheme for classical circuits proposed by Jain et al. (CRYPTO 2023) and later enhanced by Bartusek et al. (CRYPTO 2026), our obfuscation scheme can also be realized in the quantumly accessible pseudorandom oracle model.