Towards A Hybrid Quantum Differential Privacy

Fuente: arXiv
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Autori principali: Song, Baobao, Pokhrel, Shiva Raj, Vasilakos, Athanasios V., Zhu, Tianqing, Li, Gang
Natura: Preprint
Pubblicazione: 2025
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author Song, Baobao
Pokhrel, Shiva Raj
Vasilakos, Athanasios V.
Zhu, Tianqing
Li, Gang
author_facet Song, Baobao
Pokhrel, Shiva Raj
Vasilakos, Athanasios V.
Zhu, Tianqing
Li, Gang
contents Quantum computing offers unparalleled processing power but raises significant data privacy challenges. Quantum Differential Privacy (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 teh need for practical implementations beyond theoretical models. Existing QDP mechanisms, limited to single noise sources, fail to reflect teh 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 Lifted Quantum Differential Privacy, offering enhanced randomness for improved privacy audits and quantum algorithm evaluation.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07844
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Towards A Hybrid Quantum Differential Privacy
Song, Baobao
Pokhrel, Shiva Raj
Vasilakos, Athanasios V.
Zhu, Tianqing
Li, Gang
Quantum Physics
Cryptography and Security
Quantum computing offers unparalleled processing power but raises significant data privacy challenges. Quantum Differential Privacy (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 teh need for practical implementations beyond theoretical models. Existing QDP mechanisms, limited to single noise sources, fail to reflect teh 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 Lifted Quantum Differential Privacy, offering enhanced randomness for improved privacy audits and quantum algorithm evaluation.
title Towards A Hybrid Quantum Differential Privacy
topic Quantum Physics
Cryptography and Security
url https://arxiv.org/abs/2501.07844