In the Noisy Intermediate-Scale Quantum (NISQ) realm, efficient quantum circuit compilation is critical to ensure successful computation. Several third-party compilers are improving the compilation times and depth/gate counts. Untrusted third parties or a particular version of a trusted compiler may allow an attacker to steal, clone, and/or reverse engineer the quantum circuit. We propose to obfuscate quantum circuits by employing dummy CNOT gates to prevent such threats. If the adversary clones the obfuscated design, he/she will get faulty results. We propose a metric-based dummy gate insertion process to ensure maximum corruption of functionality measured using Total Variation Distance (TVD) and validated using IBM’s noisy simulators. Our metric guided dummy gate insertion process achieves TVD of up to 28.83%, and performs 10.14% better than the average TVD and performs within 12.45% of the best obtainable TVD for the test benchmarks. The removal of dummy gates by the designer post-compilation to restore functionality as well as other finer details have been addressed.
In the Noisy Intermediate-Scale Quantum (NISQ) realm, efficient quantum circuit compilation is critical to ensure successful computation. Several third-party compilers are improving the compilation times and depth/gate counts. Untrusted third parties or a particular version of a trusted compiler may allow an attacker to steal, clone, and/or reverse engineer the quantum circuit. We propose to obfuscate quantum circuits by employing dummy CNOT gates to prevent such threats. If the adversary clones the obfuscated design, he/she will get faulty results. We propose a metric-based dummy gate insertion process to ensure maximum corruption of functionality measured using Total Variation Distance (TVD) and validated using IBM’s noisy simulators. Our metric guided dummy gate insertion process achieves TVD of up to 28.83%, and performs 10.14% better than the average TVD and performs within 12.45% of the best obtainable TVD for the test benchmarks. The removal of dummy gates by the designer post-compilation to restore functionality as well as other finer details have been addressed.
Optimization of quantum circuits using an efficient compiler is key to its success for NISQ computers. Several 3rd party compilers are evolving to offer improved performance for large quantum circuits. These 3rd parties, or just a certain release of an otherwise trustworthy compiler, may possibly be untrusted and this could lead to an adversary to Reverse Engineer (RE) the quantum circuit for extracting sensitive aspects e.g., circuit topology, program, and its properties. In this paper, we propose obfuscation of quantum circuits to hide the functionality. Quantum circuits have inherent margin between correct and incorrect outputs. Therefore, obfuscation (i.e., corruption of functionality) by inserting dummy gates is nontrivial. We insert dummy SWAP gates one at a time for maximum corruption of functionality before sending the quantum circuit to an untrusted compiler. If an untrusted party clones the design, they get incorrect functionality. The designer removes the dummy SWAP gate post-compilation to restore the correct functionality. Compared to a classical counterpart, the quantum chip does not reveal the circuit functionality. Therefore, an adversary cannot guess the SWAP gate and location/validate using an oracle model. Evaluation of realistic quantum circuit with/without SWAP insertion is impossible in classical computers. Therefore, we propose a metric-based SWAP gate insertion process. The objective of the metric is to ensure maximum corruption of functionality measured using Total Variation Distance (TVD). The proposed approach is validated using IBM default noisy simulation model. Our metric-based approach predicts the SWAP position to achieve TVD of upto 50%, and performs 7.5% better than average TVD, and performs within 12.3% of the best obtainable TVD for the benchmarks. We obtain an overhead of < 5% for the number of gates and circuit depth after SWAP addition.
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).
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).
Quantum computing leverages quantum mechanics to achieve computational advantages over classical hardware, but the use of third-party quantum compilers in the Noisy Intermediate-Scale Quantum (NISQ) era introduces risks of intellectual property (IP) exposure. We address this by proposing a novel obfuscation technique that protects proprietary quantum circuits by inserting additional quantum gates prior to compilation. These gates corrupt the measurement outcomes, which are later corrected through a lightweight classical post-processing step based on the inserted gate structure. Unlike prior methods that rely on complex quantum reversals, barriers, or physical-to-virtual qubit mapping, our approach achieves obfuscation using compiler-agnostic classical correction. We evaluate the technique across five benchmark quantum algorithms—Shor’s, QAOA, Bernstein-Vazirani, Grover’s, and HHL—using IBM’s Qiskit framework. The results demonstrate high Total Variation Distance (above 0.5) and consistently negative Degree of Functional Corruption (DFC), confirming both statistical and functional obfuscation. This shows that our method is a practical and effective solution for the security of quantum circuit designs in untrusted compilation flows.
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 current phase of quantum computing is in the Noisy Intermediate-Scale Quantum (NISQ) era. On NISQ devices, two-qubit gates such as CNOTs are much noisier than single-qubit gates, so it is essential to minimize their count. Quantum circuit synthesis is a process of decomposing an arbitrary unitary into a sequence of quantum gates, and can be used as an optimization tool to produce shorter circuits to improve overall circuit fidelity. However, the time-to-solution of synthesis grows exponentially with the number of qubits. As a result, synthesis is intractable for circuits on a large qubit scale.
In this paper, we propose a hierarchical, block-by-block optimization framework, QGo, for quantum circuit optimization. Our approach allows an exponential cost optimization to scale to large circuits. QGo uses a combination of partitioning and synthesis: 1) partition the circuit into a sequence of independent circuit blocks; 2) re-generate and optimize each block using quantum synthesis; and 3) re-compose the final circuit by stitching all the blocks together. We perform our analysis and show the fidelity improvements in three different regimes: small-size circuits on real devices, medium-size circuits on noise simulations, and large-size circuits on analytical models. Using a set of NISQ benchmarks, we show that QGo can reduce the number of CNOT gates by 29.9% on average and up to 50% when compared with industrial compilers such as t|ket>. When executed on the IBM Athens system, shorter depth leads to higher circuit fidelity. We also demonstrate the scalability of our QGo technique to optimize circuits of 60+ qubits. Our technique is the first demonstration of successfully employing and scaling synthesis in the compilation toolchain for large circuits. Overall, our approach is robust for direct incorporation in production compiler toolchains.