Encryption and decryption method and system with continuous-variable quantum neural network

US2020412532A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2020412532-A1
Application numberUS-202016910594-A
CountryUS
Kind codeA1
Filing dateJun 24, 2020
Priority dateJun 28, 2019
Publication dateDec 31, 2020
Grant date

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Abstract

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A method and a system for encryption and decryption based on continuous-variable quantum neural network CVQNN. The method includes: updating a weight of the CVQNN with a training sample; triggering, by a sender, a legal measurement bases synchronization between the sender and the CVQNN; converting, by the sender, the information to be sent into a quadratic plaintext according to the synchronized measurement bases, and sending the quadratic plaintext to the CVQNN; encrypting, by the CVQNN, a received quadratic plaintext, and sending an encrypted quadratic plaintext to a receiver; after receiving the encrypted quadratic plaintext, sending by the receiver the encrypted quadratic plaintext to the CVQNN for decryption to obtain decrypted information. The embodiments implement data encryption and decryption by introducing CVQNN model and synchronization measurement technology. The embodiments provide advantages of high reliability, high security and easy realization.

First claim

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What is claimed is: 1 . An encryption and decryption method based on a continuous-variable quantum neural network (CVQNN), comprising: updating, by the CVQNN, a weight of the CVQNN with a training sample; triggering, by a sender, a legal measurement bases synchronization (LMB) between the sender and the CVQNN; converting, by the sender, information to be sent into a quadratic plaintext according to the LMB, and sending the quadratic plaintext to the CVQNN; encrypting, by the CVQNN, a received quadratic plaintext, and sending an encrypted quadratic plaintext to a receiver; and after receiving the encrypted quadratic plaintext, sending, by the receiver, the encrypted quadratic plaintext to the CVQNN for decryption to obtain decrypted information. 2 . The method according to claim 1 , wherein the updating, by the CVQNN, of the weight of the CVQNN with a training sample, comprises: repeatedly updating, by the CVQNN, the weight of the CVQNN according to the training sample until a loss value of the CVQNN loss function is less than a preset threshold. 3 . The method according to claim 2 , wherein the repeatedly updating, by the CVQNN, of the weight of the CVQNN according to the training sample until a loss value of the CVQNN loss function is less than a preset threshold, comprises: repeatedly updating, by the CVQNN, the weight of the CVQNN according to the training sample using Adam optimization algorithm, until the loss value of the CVQNN loss function is less than the preset threshold. 4 . The method according to claim 1 , wherein the triggering, by the sender, of the legal measurement bases synchronization between the sender and the CVQNN, comprises: generating, by the sender, a quantum state according to first measurement bases set and selected randomly, and sending a generated quantum state to the CVQNN; measuring, by the CVQNN, a received quantum state by using second measurement bases set and selected randomly, to obtain a first serial number, and sending the first serial number to the sender; determining, by the sender, synchronized measurement bases according to a received first serial number, and then sending the synchronized measurement bases to the CVQNN. 5 . The method according to claim 1 , wherein before the converting, by the sender, of the information to be sent into a quadratic plaintext according to the synchronized measurement bases, and sending the quadratic plaintext to the CVQNN, the method further comprises: sending, by the sender, the information to be sent to the CVQNN; if the CVQNN determines that the information to be sent is quantum state information, then sending the quantum information back to the sender; and if the CVQNN determines that the information to be sent is bit information, converting the bit information into the quantum state information through a displacement gate in vacuum state, and sending a converted quantum information to the sender. 6 . The method according to claim 1 , wherein the encrypting, by the CVQNN, of the received quadratic plaintext, and sending the encrypted quadratic plaintext to the receiver, comprises: calculating an expected value for an outputted data of the CVQNN according to the received quadratic plaintext; calculating a value of a first error correction function according to the expected value; combining a first hidden output of the CVQNN with the value of the first error correction function to obtain the encrypted quadratic plaintext; and sending the encrypted quadratic plaintext to the receiver through a communication channel. 7 . The method according to claim 1 , wherein after receiving the encrypted quadratic plaintext, the sending by the receiver the encrypted quadratic plaintext to the CVQNN for decryption to obtain decrypted information, comprises: parsing, by the receiver, the encrypted quadratic plaintext to obtain values of the second hidden output and the second error correction function of the CVQNN; sending, by the receiver, the second hidden output to the CVQNN, and receiving an output result returned by the CVQNN; and determining, by the receiver, the quadratic plaintext according to the output result and the value of the second correction function, and determining the decrypted information according to the quadratic plaintext. 8 . The method according to claim 7 , wherein after the sending by the receiver of the encrypted quadratic plaintext to the CVQNN again for decryption to obtain decrypted information, the method further comprises: sending, by the receiver, the determined quadratic plaintext to the CVQNN again, and receiving a third hidden output returned by the CVQNN; determining, by the receiver, that the information to be sent has not been maliciously modified, if the third hidden output is the same as the second hidden output; and determining, by the receiver, that the information to be sent has been modified, if the third hidden output is different from the second hidden output. 9 . An encryption and decryption system based on a continuous-variable quantum neural network (CVQNN), comprising: a sender, the CVQNN, and a receiver, wherein: the CVQNN is configured to update a weight of the CVQNN with a training sample; the sender is configured to trigger measurement bases synchronization between the sender and the CVQNN; the sender is configured to convert the information to be sent into a quadratic plaintext according to synchronized measurement bases, and send the quadratic plaintext to the CVQNN; the CVQNN is configured to encrypt a received quadratic plaintext and send an encrypted quadratic plaintext to the receiver; and the receiver is configured to send, after receiving the encrypted quadratic plaintext, the encrypted quadratic plaintext to the CVQNN for decryption to obtain decrypted information. 10 . The system according to claim 9 , wherein the CVQNN is further configured to: repeatedly update the weight of the CVQNN according to the training sample until a loss value of the CVQNN loss function is less than a preset threshold. 11 . The system according to claim 10 , wherein the CVQNN is further configured to: repeatedly update the weight of the CVQNN according to the training sample using Adam optimization algorithm, until the loss value of the CVQNN loss function is less than the preset threshold. 12 . The system according to claim 9 , wherein the sender is further configured to: generate a quantum state according to a first measurement bases set selected randomly, and send a generated quantum state to the CVQNN; and wherein the CVQNN is further configured to measure the received quantum state using a second measurement bases set selected randomly to obtain a first serial number, and sending the first serial number to the sender; and the sender is further configured to determine the synchronized measurement bases according to a received first serial number, and then send the synchronized measurement bases to the CVQNN. 13 . The system according to claim 9 , wherein the sender is further configured to: send the information to be sent to the CVQNN; and wherein the CVQNN is further configured to send quantum state information back to the sender if the CVQNN determines that the information to be sent is the quantum state information; convert, if the CVQNN determines that the information to be sent is bit information, the bit information into the quantum state information through a displacement gate in vacuum state, and send a converted quantum information to the sender. 14 . The system according to claim 9 , wherein the CVQNN is further configured to: calculate

Assignees

Inventors

Classifications

  • Transmitting and receiving encryption devices synchronised or initially set up in a particular manner · CPC title

  • Block ciphers, i.e. encrypting groups of characters of a plain text message using fixed encryption transformation · CPC title

  • H04L9/0852Primary

    Quantum cryptography (transmission systems employing electromagnetic waves other than radio waves, e.g. light, infrared H04B10/00; wavelength-division multiplex systems H04J14/02; WDM arrangements H04J14/03) · CPC title

  • involving random numbers or seeds · CPC title

  • H04L9/0858Primary

    Details about key distillation or coding, e.g. reconciliation, error correction, privacy amplification, polarisation coding or phase coding · CPC title

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What does patent US2020412532A1 cover?
A method and a system for encryption and decryption based on continuous-variable quantum neural network CVQNN. The method includes: updating a weight of the CVQNN with a training sample; triggering, by a sender, a legal measurement bases synchronization between the sender and the CVQNN; converting, by the sender, the information to be sent into a quadratic plaintext according to the synchronize…
Who is the assignee on this patent?
Univ Central South
What technology area does this patent fall under?
Primary CPC classification H04L9/0852. Mapped technology areas include Electricity.
When was this patent published?
Publication date Thu Dec 31 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).