Novel continuous-variable quantum secure direct communication and its security analysis

Chai, Geng; Cao, Zhuo‐Liang; Liu, Weiqi; Zhang, Minghui; Liang, Kexin; Peng, Jinye

doi:10.1088/1612-202x/ab3a2b

Cited by 17 publications

(10 citation statements)

References 35 publications

(44 reference statements)

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“…Moreover, the choice of von Mises prior is supported by the fact that it is a conjugate prior for a Gaussian measurement data model [48], which is the case considered in this work for phase estimation with heterodyne measurement. The von Mises distribution is parameterized by a shaping parameter κ 0 ∈ C, and has pdf [48] p(θ|κ 0 ) = 1 2πI 0 (|κ 0 |) exp Re κ 0 e −iθ (34) where I 0 (•) is the zeroth order modified Bessel function of the first kind. The mean of this distribution is E[θ] = ∠κ 0 .…”

Section: Phase Estimationmentioning

confidence: 99%

“…The following proposition summarizes the conjugate prior result for a von Mises prior with Gaussian measurement model. Proposition 1: Let the prior distribution of the unknown phase parameter θ be a von Mises distribution with parameter κ 0 , such that the pdf is given by (34). If the likelihood of the observed data y ∈ C M ×1 is Gaussian, i.e., p(y|θ) = CN e −iθ x, σ 2 I M , then the posterior distribution of θ is also von Mises with parameter κ p = κ 0 + 2 σ 2 y H x [48].…”

Section: Phase Estimationmentioning

confidence: 99%

“…( 7)-( 9)]. Using Proposition 1 along with (33), (34), the posterior distribution of θ is given by [48]…”

Section: Phase Estimationmentioning

confidence: 99%

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Machine-Learning-Based Parameter Estimation of Gaussian Quantum States

Kundu¹,

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We propose a machine learning framework for parameter estimation of single mode Gaussian quantum states. Under a Bayesian framework, our approach estimates parameters of suitable prior distributions from measured data. For phase-space displacement and squeezing parameter estimation, this is achieved by introducing Expectation-Maximization (EM) based algorithms, while for phase parameter estimation an empirical Bayes method is applied. The estimated prior distribution parameters along with the observed data are used for finding the optimal Bayesian estimate of the unknown displacement, squeezing and phase parameters. Our simulation results show that the proposed algorithms have estimation performance that is very close to that of 'Genie Aided' Bayesian estimators, that assume perfect knowledge of the prior parameters. In practical scenarios, when numerical values of the prior distribution parameters are not known beforehand, our proposed methods can be used to find optimal Bayesian estimates from the observed measurement data.

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Section: Phase Estimationmentioning

confidence: 99%

Section: Phase Estimationmentioning

confidence: 99%

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Machine-Learning-Based Parameter Estimation of Gaussian Quantum States

Kundu¹,

McKay²,

Mallik³

2022

IEEE Trans. Quantum Eng.

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“…Nevertheless, the enormous computing power of the quantum computer will threaten the classical multisig protocols with only mathematically difficult embedded cryptography [5], [6]. To withstand the attacks of quantum computing, a series of secure communication protocols has been developed using quantum algorithms, including quantum key distribution (QKD) [7]- [9], quantum secret sharing (QSS) [10], [11], quantum secure direct communication (QSDC) [12]- [14], quantum private comparison (QPC) [15]- [17] and quantum identity authentication (QIA) [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Sequential Quantum Multiparty Signature Based on Quantum Fourier Transform and Chaotic System

et al. 2020

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Motivated by the quantum Fourier transform (QFT), a sequential quantum multiparty signature (QMS) scheme is proposed. Several signatories jointly accomplish the task in a chaotic encryption system. Alice generates and sends the encrypted message with the quantum Fourier transform. Signatories provide individual signatures in a certain order, while Bob verifies the authenticity of the combined multiple signatures after the eavesdropping check phase with help of the arbitrator. Analysis shows the correctness and security of the proposed scheme. This QMS protocol increases the efficiency of verification compared to arbitrated quantum signatures and broadcasting multiparty signature. This QMS protocol will be widely used for online e-government and e-business systems.

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“…In 2018 and 2020, the MDI-QSDC protocols based on entanglement and single photons were proposed, respectively [41,42]. Subsequently, researchers proposed some other interesting QSDC protocols [43][44][45][46][47][48][49][50][51].…”

mentioning

confidence: 99%

Measurement-device–independent quantum secure direct communication of multiple degrees of freedom of a single photon

Zou¹,

Zhou²,

Zhong³

et al. 2020

EPL

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Quantum secure direct communication (QSDC) can realize the direct and secure transmission of information instead of sharing secure keys between two parties. Similar to quantum key distribution (QKD), in practical applications, QSDC may suffer from attacks from imperfect detector. Measurement-device-independent QSDC (MDI-QSDC) can remove all attacks at detector's side and close all loopholes in the detection system. However, existing MDI-QSDC protocols have relatively low capacity. In this paper, we propose a high-capacity MDI-QSDC protocol of multiple degrees of freedom of a single photon. Compared with original MDI-QSDC protocols, our protocol has larger channel capacity which can use a single photon to transmit multi-bit of secure information. This protocol may have potential application in future quantum secure communication.

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Novel continuous-variable quantum secure direct communication and its security analysis

Cited by 17 publications

References 35 publications

Machine-Learning-Based Parameter Estimation of Gaussian Quantum States

Machine-Learning-Based Parameter Estimation of Gaussian Quantum States

Sequential Quantum Multiparty Signature Based on Quantum Fourier Transform and Chaotic System

Measurement-device–independent quantum secure direct communication of multiple degrees of freedom of a single photon

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