Quantum secure two-party Euclidean distance computation based on mutually unbiased bases View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2022-07-26

AUTHORS

Yinhong Cao

ABSTRACT

Quantum secure multi-party geometry computation is a specific primitive of classical secure multi-party computation. Compared with classical secure multi-party geometry computation based on mathematical difficulty problems which have been potentially threatened due to the development of quantum computer technology, the quantum protocol can provide unconditional security for the geometry computation. A novel quantum protocol based on the mutually biased bases of d-level quantum system is constructed to perform secure two-party Euclidean distance computation. With the aid of a semi-honest third party, the proposed protocol can calculate the Euclidean distance between two secret n-dimensional coordinates held by the participants who do not trust each other. Not only can the protocol resist the attacks from both outside eavesdroppers and participants, but also from semi-honest third party who does not collude with any participant. More... »

PAGES

262

References to SciGraph publications

  • 2001-08-02. Secure Multi-party Computational Geometry in ALGORITHMS AND DATA STRUCTURES
  • 2012-06-22. Comment on quantum private comparison protocols with a semi-honest third party in QUANTUM INFORMATION PROCESSING
  • 2005-03. Secure Two-Party Computational Geometry in JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
  • 2017-11-14. A novel quantum scheme for secure two-party distance computation in QUANTUM INFORMATION PROCESSING
  • 2018-05-04. A novel quantum solution to secure two-party distance computation in QUANTUM INFORMATION PROCESSING
  • 2019-01-18. Quantum private query: A new kind of practical quantum cryptographic protocol in SCIENCE CHINA PHYSICS, MECHANICS & ASTRONOMY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11128-022-03611-9

    DOI

    http://dx.doi.org/10.1007/s11128-022-03611-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1149786460


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Physical Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0206", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Quantum Physics", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "School of Mathematics and Information Science, Henan Polytechnic University, 454003, Jiaozuo, People\u2019s Republic of China", 
              "id": "http://www.grid.ac/institutes/grid.412097.9", 
              "name": [
                "School of Mathematics and Information Science, Henan Polytechnic University, 454003, Jiaozuo, People\u2019s Republic of China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cao", 
            "givenName": "Yinhong", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/3-540-44634-6_16", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033418528", 
              "https://doi.org/10.1007/3-540-44634-6_16"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11128-018-1911-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103811873", 
              "https://doi.org/10.1007/s11128-018-1911-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11433-018-9324-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1111603757", 
              "https://doi.org/10.1007/s11433-018-9324-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11390-005-0258-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019880980", 
              "https://doi.org/10.1007/s11390-005-0258-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11128-017-1766-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092691710", 
              "https://doi.org/10.1007/s11128-017-1766-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11128-012-0433-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001805724", 
              "https://doi.org/10.1007/s11128-012-0433-4"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2022-07-26", 
        "datePublishedReg": "2022-07-26", 
        "description": "Quantum secure multi-party geometry computation is a specific primitive of classical secure multi-party computation. Compared with classical secure multi-party geometry computation based on mathematical difficulty problems which have been potentially threatened due to the development of quantum computer technology, the quantum protocol can provide unconditional security for the geometry computation. A novel quantum protocol based on the mutually biased bases of d-level quantum system is constructed to perform secure two-party Euclidean distance computation. With the aid of a semi-honest third party, the proposed protocol can calculate the Euclidean distance between two secret n-dimensional coordinates held by the participants who do not trust each other. Not only can the protocol resist the attacks from both outside eavesdroppers and participants, but also from semi-honest third party who does not collude with any participant.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s11128-022-03611-9", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1052742", 
            "issn": [
              "1570-0755", 
              "1573-1332"
            ], 
            "name": "Quantum Information Processing", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "7", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "21"
          }
        ], 
        "keywords": [
          "geometry computation", 
          "quantum computer technology", 
          "d-level quantum system", 
          "quantum protocols", 
          "Euclidean distance computation", 
          "quantum systems", 
          "distance computation", 
          "secure multi-party computation", 
          "semi-honest third party", 
          "multi-party computation", 
          "computation", 
          "third party", 
          "unbiased bases", 
          "biased bases", 
          "computer technology", 
          "specific primitives", 
          "novel quantum protocol", 
          "unconditional security", 
          "difficulty problem", 
          "Euclidean distance", 
          "outside eavesdropper", 
          "dimensional coordinates", 
          "quantum", 
          "coordinates", 
          "problem", 
          "protocol", 
          "primitives", 
          "security", 
          "eavesdropper", 
          "attacks", 
          "technology", 
          "system", 
          "parties", 
          "distance", 
          "basis", 
          "aid", 
          "development", 
          "participants"
        ], 
        "name": "Quantum secure two-party Euclidean distance computation based on mutually unbiased bases", 
        "pagination": "262", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1149786460"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s11128-022-03611-9"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s11128-022-03611-9", 
          "https://app.dimensions.ai/details/publication/pub.1149786460"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-10-01T06:50", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/article/article_937.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s11128-022-03611-9"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11128-022-03611-9'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11128-022-03611-9'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11128-022-03611-9'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11128-022-03611-9'


     

    This table displays all metadata directly associated to this object as RDF triples.

    118 TRIPLES      21 PREDICATES      68 URIs      54 LITERALS      6 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s11128-022-03611-9 schema:about anzsrc-for:02
    2 anzsrc-for:0206
    3 schema:author N94bff18b02f9471eb205a6cdb5fa422a
    4 schema:citation sg:pub.10.1007/3-540-44634-6_16
    5 sg:pub.10.1007/s11128-012-0433-4
    6 sg:pub.10.1007/s11128-017-1766-9
    7 sg:pub.10.1007/s11128-018-1911-0
    8 sg:pub.10.1007/s11390-005-0258-z
    9 sg:pub.10.1007/s11433-018-9324-6
    10 schema:datePublished 2022-07-26
    11 schema:datePublishedReg 2022-07-26
    12 schema:description Quantum secure multi-party geometry computation is a specific primitive of classical secure multi-party computation. Compared with classical secure multi-party geometry computation based on mathematical difficulty problems which have been potentially threatened due to the development of quantum computer technology, the quantum protocol can provide unconditional security for the geometry computation. A novel quantum protocol based on the mutually biased bases of d-level quantum system is constructed to perform secure two-party Euclidean distance computation. With the aid of a semi-honest third party, the proposed protocol can calculate the Euclidean distance between two secret n-dimensional coordinates held by the participants who do not trust each other. Not only can the protocol resist the attacks from both outside eavesdroppers and participants, but also from semi-honest third party who does not collude with any participant.
    13 schema:genre article
    14 schema:isAccessibleForFree false
    15 schema:isPartOf N44c78156f5c8483ba126daaa298cd871
    16 Nc522997714b944b082907af036aa7014
    17 sg:journal.1052742
    18 schema:keywords Euclidean distance
    19 Euclidean distance computation
    20 aid
    21 attacks
    22 basis
    23 biased bases
    24 computation
    25 computer technology
    26 coordinates
    27 d-level quantum system
    28 development
    29 difficulty problem
    30 dimensional coordinates
    31 distance
    32 distance computation
    33 eavesdropper
    34 geometry computation
    35 multi-party computation
    36 novel quantum protocol
    37 outside eavesdropper
    38 participants
    39 parties
    40 primitives
    41 problem
    42 protocol
    43 quantum
    44 quantum computer technology
    45 quantum protocols
    46 quantum systems
    47 secure multi-party computation
    48 security
    49 semi-honest third party
    50 specific primitives
    51 system
    52 technology
    53 third party
    54 unbiased bases
    55 unconditional security
    56 schema:name Quantum secure two-party Euclidean distance computation based on mutually unbiased bases
    57 schema:pagination 262
    58 schema:productId N384d1007473d43c68ded93a6d14e7224
    59 N6eb822c323fd45bfa557f257ae5d44c1
    60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1149786460
    61 https://doi.org/10.1007/s11128-022-03611-9
    62 schema:sdDatePublished 2022-10-01T06:50
    63 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    64 schema:sdPublisher N5650d6faa50e44fd80f6495214cc5e4d
    65 schema:url https://doi.org/10.1007/s11128-022-03611-9
    66 sgo:license sg:explorer/license/
    67 sgo:sdDataset articles
    68 rdf:type schema:ScholarlyArticle
    69 N384d1007473d43c68ded93a6d14e7224 schema:name dimensions_id
    70 schema:value pub.1149786460
    71 rdf:type schema:PropertyValue
    72 N44c78156f5c8483ba126daaa298cd871 schema:issueNumber 7
    73 rdf:type schema:PublicationIssue
    74 N5650d6faa50e44fd80f6495214cc5e4d schema:name Springer Nature - SN SciGraph project
    75 rdf:type schema:Organization
    76 N6eb822c323fd45bfa557f257ae5d44c1 schema:name doi
    77 schema:value 10.1007/s11128-022-03611-9
    78 rdf:type schema:PropertyValue
    79 N94bff18b02f9471eb205a6cdb5fa422a rdf:first Ne4a6fdb695354cb5bc510f43266e87ec
    80 rdf:rest rdf:nil
    81 Nc522997714b944b082907af036aa7014 schema:volumeNumber 21
    82 rdf:type schema:PublicationVolume
    83 Ne4a6fdb695354cb5bc510f43266e87ec schema:affiliation grid-institutes:grid.412097.9
    84 schema:familyName Cao
    85 schema:givenName Yinhong
    86 rdf:type schema:Person
    87 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
    88 schema:name Physical Sciences
    89 rdf:type schema:DefinedTerm
    90 anzsrc-for:0206 schema:inDefinedTermSet anzsrc-for:
    91 schema:name Quantum Physics
    92 rdf:type schema:DefinedTerm
    93 sg:journal.1052742 schema:issn 1570-0755
    94 1573-1332
    95 schema:name Quantum Information Processing
    96 schema:publisher Springer Nature
    97 rdf:type schema:Periodical
    98 sg:pub.10.1007/3-540-44634-6_16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033418528
    99 https://doi.org/10.1007/3-540-44634-6_16
    100 rdf:type schema:CreativeWork
    101 sg:pub.10.1007/s11128-012-0433-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001805724
    102 https://doi.org/10.1007/s11128-012-0433-4
    103 rdf:type schema:CreativeWork
    104 sg:pub.10.1007/s11128-017-1766-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092691710
    105 https://doi.org/10.1007/s11128-017-1766-9
    106 rdf:type schema:CreativeWork
    107 sg:pub.10.1007/s11128-018-1911-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103811873
    108 https://doi.org/10.1007/s11128-018-1911-0
    109 rdf:type schema:CreativeWork
    110 sg:pub.10.1007/s11390-005-0258-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1019880980
    111 https://doi.org/10.1007/s11390-005-0258-z
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1007/s11433-018-9324-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111603757
    114 https://doi.org/10.1007/s11433-018-9324-6
    115 rdf:type schema:CreativeWork
    116 grid-institutes:grid.412097.9 schema:alternateName School of Mathematics and Information Science, Henan Polytechnic University, 454003, Jiaozuo, People’s Republic of China
    117 schema:name School of Mathematics and Information Science, Henan Polytechnic University, 454003, Jiaozuo, People’s Republic of China
    118 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...