AUTO-ADAPTIVE INTERVAL SELECTION ALGORITHM FOR QUANTUM KEY DISTRIBUTION

被引:0
|
作者
Han, Jiajing [1 ]
Qian, Xudong [2 ]
机构
[1] Fudan Univ, Dept Phys, Shanghai 200433, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Elect Engn, State Key Lab Adv Opt Commun Syst & Networks, Shanghai 200030, Peoples R China
关键词
Reconciliation; Winnow protocol; Auto-adaptive Interval Selection Algorithm; CRYPTOGRAPHY;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Key reconciliation plays an important role in quantum key distribution, as well as shared bit string distillation. To distill efficiently the final key a so-called Winnow protocol has been proposed. However, how to choose the interval length of the shared string to maximize the Winnow efficiency is difficult in practical program processing. Because the interval choice remains an open problem the key rate of the Winnow protocol is not as high as the one calculated in theory. Consequently, the Winnow protocol is difficult to efficiently employ in application. In this paper we first analytically investigate the dependence of the interval length on the error distribution and the code. Then ail auto-adaptive interval selection algorithm is proposed. In addition, new characteristics of the protocol are investigated.
引用
收藏
页码:693 / 700
页数:8
相关论文
共 50 条
  • [31] An auto-adaptive background subtraction method for Raman spectra
    Xie, Yi
    Yang, Lidong
    Sun, Xilong
    Wu, Dewen
    Chen, Qizhen
    Zeng, Yongming
    Liu, Guokun
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2016, 161 : 58 - 63
  • [32] A Design of Time-varying Auto-adaptive Tracker
    Wang, Xianfang
    Du, Zhiyong
    Pan, Feng
    2008 ISECS INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT, VOL 1, PROCEEDINGS, 2008, : 409 - +
  • [33] Passive auto-adaptive seismic resistant structures and their development
    Ye, LP
    Qazi, AU
    Wang, XL
    PROCEEDINGS OF THE EIGHTH INTERNATIONAL SYMPOSIUM ON STRUCTURAL ENGINEERING FOR YOUNG EXPERTS, VOLS 1 AND 2, 2004, : 303 - 309
  • [34] An auto-adaptive sub-stepping algorithm for phase-field modeling of brittle fracture
    Gupta, Abhinav
    Krishnan, U. Meenu
    Chowdhury, Rajib
    Chakrabarti, Anupam
    THEORETICAL AND APPLIED FRACTURE MECHANICS, 2020, 108
  • [35] An Auto-adaptive CNN for Crowd Counting in Monitor Image
    Chang, Qiu
    Qi, Yonggang
    Zhou, Wenli
    Liu, Jun
    PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON NETWORK INFRASTRUCTURE AND DIGITAL CONTENT (IEEE IC-NIDC), 2018, : 40 - 44
  • [36] Auto-Adaptive Ultra-Low Power IC
    Bosio, A.
    Debaud, P.
    Girard, P.
    Guilhot, S.
    Valka, M.
    Virazel, A.
    2016 11TH IEEE INTERNATIONAL CONFERENCE ON DESIGN & TECHNOLOGY OF INTEGRATED SYSTEMS IN NANOSCALE ERA (DTIS), 2016,
  • [37] AFCMAC: an Auto-adaptive Fuzzy CMAC for Oculomotor System
    Ghassemi, Elham
    Kapoula, Zoi
    2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2012,
  • [38] Distributive Justice for Fair Auto-adaptive Clusters of Connected Vehicles
    Garbiso, Julian
    Diaconescu, Ada
    Coupechoux, Marceau
    Pitt, Jeremy
    Leroy, Bertrand
    2017 IEEE 2ND INTERNATIONAL WORKSHOPS ON FOUNDATIONS AND APPLICATIONS OF SELF* SYSTEMS (FAS*W), 2017, : 79 - 84
  • [39] Active auto-adaptive metamaterial plates for flexural wave control
    Li, Zheng-Yang
    Ma, Tian-Xue
    Wang, Yan-Zheng
    Chai, Yu-Yang
    Zhang, Chuanzeng
    Li, Feng-Ming
    INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES, 2022, 254
  • [40] Self-actuating fiber composites for auto-adaptive structures
    Krstulovic-Opara, N
    Wriggers, P
    Krstulovic-Opara, L
    SMART STRUCTURES AND MATERIALS 2001: SMART SYSTEMS FOR BRIDGES, STRUCTURES, AND HIGHWAYS, 2001, 4330 : 416 - 425