Continuous-variable quantum computing on encrypted data

The ability to perform computations on encrypted data is a powerful tool for protecting a client’s privacy, especially in today’s era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the...

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Published in:Nature communications Vol. 7; no. 1; pp. 13795 - 7
Main Authors: Marshall, Kevin, Jacobsen, Christian S., Schäfermeier, Clemens, Gehring, Tobias, Weedbrook, Christian, Andersen, Ulrik L.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 14.12.2016
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Abstract The ability to perform computations on encrypted data is a powerful tool for protecting a client’s privacy, especially in today’s era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker’s computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user’s privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks. Performing computation on encrypted data is a power tool for protecting a client’s privacy, but the best solutions achieved by classical approaches are only computationally secure. Here authors present and experimentally demonstrate a quantum protocol to achieve this using continuous variables.
AbstractList The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks. Performing computation on encrypted data is a power tool for protecting a client's privacy, but the best solutions achieved by classical approaches are only computationally secure. Here authors present and experimentally demonstrate a quantum protocol to achieve this using continuous variables.
The ability to perform computations on encrypted data is a powerful tool for protecting a client’s privacy, especially in today’s era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker’s computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user’s privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks.
Performing computation on encrypted data is a power tool for protecting a client’s privacy, but the best solutions achieved by classical approaches are only computationally secure. Here authors present and experimentally demonstrate a quantum protocol to achieve this using continuous variables.
The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks.The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker's computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user's privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks.
ArticleNumber 13795
Author Gehring, Tobias
Andersen, Ulrik L.
Jacobsen, Christian S.
Schäfermeier, Clemens
Weedbrook, Christian
Marshall, Kevin
Author_xml – sequence: 1
  givenname: Kevin
  surname: Marshall
  fullname: Marshall, Kevin
  email: marshall@physics.utoronto.ca
  organization: Department of Physics, University of Toronto
– sequence: 2
  givenname: Christian S.
  surname: Jacobsen
  fullname: Jacobsen, Christian S.
  organization: Department of Physics, Technical University of Denmark
– sequence: 3
  givenname: Clemens
  surname: Schäfermeier
  fullname: Schäfermeier, Clemens
  organization: Department of Physics, Technical University of Denmark
– sequence: 4
  givenname: Tobias
  surname: Gehring
  fullname: Gehring, Tobias
  email: tobias.gehring@fysik.dtu.dk
  organization: Department of Physics, Technical University of Denmark
– sequence: 5
  givenname: Christian
  surname: Weedbrook
  fullname: Weedbrook, Christian
  email: christian.weedbrook@gmail.com
  organization: CipherQ
– sequence: 6
  givenname: Ulrik L.
  surname: Andersen
  fullname: Andersen, Ulrik L.
  organization: Department of Physics, Technical University of Denmark
BackLink https://www.ncbi.nlm.nih.gov/pubmed/27966528$$D View this record in MEDLINE/PubMed
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Snippet The ability to perform computations on encrypted data is a powerful tool for protecting a client’s privacy, especially in today’s era of cloud and distributed...
The ability to perform computations on encrypted data is a powerful tool for protecting a client's privacy, especially in today's era of cloud and distributed...
Performing computation on encrypted data is a power tool for protecting a client’s privacy, but the best solutions achieved by classical approaches are only...
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Cloud computing
Computer applications
Computer networks
Continuity (mathematics)
Distributed processing
Encryption
Humanities and Social Sciences
multidisciplinary
Privacy
Quantum computing
Science
Science (multidisciplinary)
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