Toward a Hybrid Quantum Differential Privacy
Quantum computing offers unparalleled processing power but raises significant data privacy challenges. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Quantum Differential Privacy</i> (QDP) leverages inherent quantum noise to safeguard privacy, surpassing traditional DP. This paper develops comprehensive noise profiles, identifies noise types beneficial for QDP, and highlights the need for practical implementations beyond theoretical models. Existing QDP mechanisms, limited to single noise sources, fail to reflect the multi-source noise reality of quantum systems. We propose a resilient hybrid QDP mechanism utilizing channel and measurement noise, optimizing privacy budgets to balance privacy and utility. Additionally, we introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lifted Quantum Differential Privacy</i>, offering enhanced randomness for improved privacy audits and quantum algorithm evaluation.
Authors
- Baobao Song (ORCID: https://orcid.org/0000-0001-6010-1055)
- Tianqing Zhu (ORCID: https://orcid.org/0000-0003-3411-7947)
- Shiva Raj Pokhrel (ORCID: https://orcid.org/0000-0001-5819-765X)
- Athanasios V. Vasilakos (ORCID: https://orcid.org/0000-0003-1902-9877)
- Gang Li (ORCID: https://orcid.org/0000-0003-1583-641X)
Institutions
- University of Technology Sydney (AU)
- Deakin University (AU)
- City University of Macau (MO)
- Imam Abdulrahman Bin Faisal University (SA)
Publication Details
- Journal
- IEEE Journal on Selected Areas in Communications
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1109/jsac.2025.3568046
- Citations
- 1
- Primary Topic
- Quantum Information and Cryptography
- Type
- article
- Field-Weighted Citation Impact
- 2.48