Differential Privacy in Quantum Computation

Publication Type:
Conference Proceeding
Citation:
Proceedings - IEEE Computer Security Foundations Symposium, 2017, pp. 249 - 262
Issue Date:
2017-09-25
Full metadata record
Files in This Item:
Filename Description Size
08049724.pdfPublished version318.01 kB
Adobe PDF
© 2017 IEEE. More and more quantum algorithms have been designed for solving problems in machine learning, database search and data analytics. An important problem then arises: how privacy can be protected when these algorithms are used on private data? For classical computing, the notion of differential privacy provides a very useful conceptual framework in which a great number of mechanisms that protect privacy by introducing certain noises into algorithms have been successfully developed. This paper defines a notion of differential privacy for quantum information processing. We carefully examine how the mechanisms using three important types of quantum noise, the amplitude/phase damping and depolarizing, can protect differential privacy. A composition theorem is proved that enables us to combine multiple privacy-preserving operations in quantum information processing.
Please use this identifier to cite or link to this item: