“Privacy-preserving quantum machine learning using differential privacy,”
Abstract
The advance of artificial intelligence in general and machine learning in particular has resulted in the need to pay more attention to the provision of privacy to the data being anlyzed. An example of sensitive data analysis might be in the analysis of individuals' medical records. In such a case, there might be a need to draw insights from data while at the same time maintaining privacy of the participants. Such cases have given birth to privacy-preserving data analyitics. Privacy is typically guaranteed by a differentially private mechanism. In this paper, we present a novel mechanism for privacy-preserving quantum machine learning. The mechanism is tested on the sensitive dataset that contains features and target labels for breast cancer prediction. The results obtained underline the utility of this mechanism.
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Quantum technologies can provide secure transmission of medical data, ensuring privacy and confidentiality.
“QTs can provide secure transmission of medical data, ensuring privacy (Senekane et al., 2017; Senekane, 2019) and confidentiality (Garapo et al., 2016; Mafu and Senekane, 2018).”
From Quantum technology for development framework as a tool for science diplomacy (2023) · cites this paper as Senekane et al., 2017
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References 18 · Cited by 25
- Authors
- Senekane, M., Mafu, M., & Taele, B. M.
- Affiliations
- National University of Lesotho (LS)
- Botswana International University of Science and Technology (BW)
- Venue
- 2017 IEEE AFRICON
- Publisher
- IEEE
- Published
- 2017-09
- Pages
- 1432-1435
- OpenAlex
- W2770184677
- Cited by
- 25
- References
- 18
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 5 · 2023: 7 · 2022: 3 · 2021: 2 · 2019: 2
- FWCI
- 0.25
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE AFRICON (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Keywords
- privacy-preserving machine learning, quantum machine learning, differential privacy, medical data privacy, breast cancer prediction
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