TY - GEN
T1 - Enhanced Local Differential Privacy Protection Against Crosstalk Attacks in Quantum Computing
AU - Zhong, Hui
AU - Zhang, Xinyue
AU - Wang, Hao
AU - Yu, Shucheng
AU - Wang, Yu
AU - Pan, Miao
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Quantum computing has gained widespread interest due to its exponential computational capabilities. In practical scenarios, users often access real quantum computers indirectly through cloud-based platforms (e.g., IBM Quantum), which requires transmitting data to third-party servers. Quantum-specific attacks, such as crosstalk attacks, have demonstrated high success rates in inferring the output of legitimate users. These issues raise serious privacy concerns. To protect client-side privacy, quantum local differential privacy (QLDP) has been proposed, where legitimate users perturbed their true output by adding quantum noise to the circuits. However, we observe that the classical local differential privacy (LDP) properties have not been fully adapted to the quantum domain, and the information can still be inferred from the perturbed output if attackers access the noise type added by legitimate users. To fill this gap, we propose a novel QLDP-based approach to protect the true output of legitimate users. We find that QLDP can be achieved using only simple quantum noise, but not all types of quantum noise can effectively perturb the output under different quantum measurements. In addition, to prevent advanced attackers who have partial user information, we introduce a probabilistic noise addition mechanism. To allow legitimate users to accurately estimate the true output of a quantum circuit, we also propose a new quantum frequency estimation. Our approach is validated using real quantum computers and quantum simulators, achieving 94% accuracy and 90% utility to estimate the true output from the perturbed output.
AB - Quantum computing has gained widespread interest due to its exponential computational capabilities. In practical scenarios, users often access real quantum computers indirectly through cloud-based platforms (e.g., IBM Quantum), which requires transmitting data to third-party servers. Quantum-specific attacks, such as crosstalk attacks, have demonstrated high success rates in inferring the output of legitimate users. These issues raise serious privacy concerns. To protect client-side privacy, quantum local differential privacy (QLDP) has been proposed, where legitimate users perturbed their true output by adding quantum noise to the circuits. However, we observe that the classical local differential privacy (LDP) properties have not been fully adapted to the quantum domain, and the information can still be inferred from the perturbed output if attackers access the noise type added by legitimate users. To fill this gap, we propose a novel QLDP-based approach to protect the true output of legitimate users. We find that QLDP can be achieved using only simple quantum noise, but not all types of quantum noise can effectively perturb the output under different quantum measurements. In addition, to prevent advanced attackers who have partial user information, we introduce a probabilistic noise addition mechanism. To allow legitimate users to accurately estimate the true output of a quantum circuit, we also propose a new quantum frequency estimation. Our approach is validated using real quantum computers and quantum simulators, achieving 94% accuracy and 90% utility to estimate the true output from the perturbed output.
KW - Quantum computing
KW - Quantum local differential privacy
KW - Quantum privacy
UR - https://www.scopus.com/pages/publications/105030192969
UR - https://www.scopus.com/pages/publications/105030192969#tab=citedBy
U2 - 10.1109/QCE65121.2025.00019
DO - 10.1109/QCE65121.2025.00019
M3 - Conference contribution
AN - SCOPUS:105030192969
T3 - Proceedings - IEEE Quantum Week 2025, QCE 2025
SP - 76
EP - 86
BT - Technical Papers Program
A2 - Culhane, Candace
A2 - Byrd, Greg
A2 - Muller, Hausi
A2 - Delgado, Andrea
A2 - Eidenbenz, Stephan
T2 - 6th IEEE International Conference on Quantum Computing and Engineering, QCE 2025
Y2 - 31 August 2025 through 5 September 2025
ER -