Decomposition+: Improving ℓ-Diversity for Multiple Sensitive Attributes View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2012

AUTHORS

Devayon Das , Dhruba K. Bhattacharyya

ABSTRACT

In this paper, we analyse existing privacy-transformation techniques in the field of PPDP that anonymize datasets with Multiple Sensitive Attributes (MSA). Of these, we present an analysis of Decomposition, an algorithm which generates a dataset with distinct ℓ-diversity over MSA using a partitioning approach. We discuss some improvements which can be made over Decomposition: in the realms of its running time, its data utility, and its applicability in the case of Multiple Release Publishing. To this effect, we describe Decomposition+ an algorithm that implements some of these improvements and is thus more suited for use in real-life scenarios. More... »

PAGES

403-412

References to SciGraph publications

  • 2006. Secure Anonymization for Incremental Datasets in SECURE DATA MANAGEMENT
  • 2009. Decomposition: Privacy Preservation for Multiple Sensitive Attributes in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • Book

    TITLE

    Advances in Computer Science and Information Technology. Computer Science and Engineering

    ISBN

    978-3-642-27307-0
    978-3-642-27308-7

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-27308-7_44

    DOI

    http://dx.doi.org/10.1007/978-3-642-27308-7_44

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1040769956


    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/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Tezpur University", 
              "id": "https://www.grid.ac/institutes/grid.45982.32", 
              "name": [
                "Department of Computer Science and Engineering, Tezpur University, 784028, India"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Das", 
            "givenName": "Devayon", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Tezpur University", 
              "id": "https://www.grid.ac/institutes/grid.45982.32", 
              "name": [
                "Department of Computer Science and Engineering, Tezpur University, 784028, India"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bhattacharyya", 
            "givenName": "Dhruba K.", 
            "id": "sg:person.013176727273.61", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013176727273.61"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1145/1749603.1749605", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022201886"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4018/jisp.2008070103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024502091"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11844662_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041922259", 
              "https://doi.org/10.1007/11844662_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11844662_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041922259", 
              "https://doi.org/10.1007/11844662_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-00887-0_42", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047208706", 
              "https://doi.org/10.1007/978-3-642-00887-0_42"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-00887-0_42", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047208706", 
              "https://doi.org/10.1007/978-3-642-00887-0_42"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1217299.1217302", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049597398"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tkde.2009.139", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061662003"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/s0218488502001648", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062976751"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/s021848850200165x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062976752"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3724/sp.j.1016.2008.00574", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1071325558"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icde.2007.367856", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093296979"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/ictm.2009.5412903", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094463223"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icde.2007.367857", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095743702"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2012", 
        "datePublishedReg": "2012-01-01", 
        "description": "In this paper, we analyse existing privacy-transformation techniques in the field of PPDP that anonymize datasets with Multiple Sensitive Attributes (MSA). Of these, we present an analysis of Decomposition, an algorithm which generates a dataset with distinct \u2113-diversity over MSA using a partitioning approach. We discuss some improvements which can be made over Decomposition: in the realms of its running time, its data utility, and its applicability in the case of Multiple Release Publishing. To this effect, we describe Decomposition+ an algorithm that implements some of these improvements and is thus more suited for use in real-life scenarios.", 
        "editor": [
          {
            "familyName": "Meghanathan", 
            "givenName": "Natarajan", 
            "type": "Person"
          }, 
          {
            "familyName": "Chaki", 
            "givenName": "Nabendu", 
            "type": "Person"
          }, 
          {
            "familyName": "Nagamalai", 
            "givenName": "Dhinaharan", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-642-27308-7_44", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": {
          "isbn": [
            "978-3-642-27307-0", 
            "978-3-642-27308-7"
          ], 
          "name": "Advances in Computer Science and Information Technology. Computer Science and Engineering", 
          "type": "Book"
        }, 
        "name": "Decomposition+: Improving \u2113-Diversity for Multiple Sensitive Attributes", 
        "pagination": "403-412", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-642-27308-7_44"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "c23615a4ba12ef0c8f9be7051dd41d97a32457eda75569a08cd1db2be942c7cd"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1040769956"
            ]
          }
        ], 
        "publisher": {
          "location": "Berlin, Heidelberg", 
          "name": "Springer Berlin Heidelberg", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-642-27308-7_44", 
          "https://app.dimensions.ai/details/publication/pub.1040769956"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T13:30", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8664_00000268.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-3-642-27308-7_44"
      }
    ]
     

    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.10.1007/978-3-642-27308-7_44'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-27308-7_44'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-27308-7_44'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-27308-7_44'


     

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

    119 TRIPLES      23 PREDICATES      39 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-642-27308-7_44 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author Nd5d15aa782aa4ed5a396a17b487f2737
    4 schema:citation sg:pub.10.1007/11844662_4
    5 sg:pub.10.1007/978-3-642-00887-0_42
    6 https://doi.org/10.1109/icde.2007.367856
    7 https://doi.org/10.1109/icde.2007.367857
    8 https://doi.org/10.1109/ictm.2009.5412903
    9 https://doi.org/10.1109/tkde.2009.139
    10 https://doi.org/10.1142/s0218488502001648
    11 https://doi.org/10.1142/s021848850200165x
    12 https://doi.org/10.1145/1217299.1217302
    13 https://doi.org/10.1145/1749603.1749605
    14 https://doi.org/10.3724/sp.j.1016.2008.00574
    15 https://doi.org/10.4018/jisp.2008070103
    16 schema:datePublished 2012
    17 schema:datePublishedReg 2012-01-01
    18 schema:description In this paper, we analyse existing privacy-transformation techniques in the field of PPDP that anonymize datasets with Multiple Sensitive Attributes (MSA). Of these, we present an analysis of Decomposition, an algorithm which generates a dataset with distinct ℓ-diversity over MSA using a partitioning approach. We discuss some improvements which can be made over Decomposition: in the realms of its running time, its data utility, and its applicability in the case of Multiple Release Publishing. To this effect, we describe Decomposition+ an algorithm that implements some of these improvements and is thus more suited for use in real-life scenarios.
    19 schema:editor N7522e152436e402c949db9d44108b1f9
    20 schema:genre chapter
    21 schema:inLanguage en
    22 schema:isAccessibleForFree true
    23 schema:isPartOf N06283689527d4d149d3d0cc12a04c438
    24 schema:name Decomposition+: Improving ℓ-Diversity for Multiple Sensitive Attributes
    25 schema:pagination 403-412
    26 schema:productId N21506b97ca0844e0afed6dda48a4101c
    27 N61884f62f30143efb18656a60ae66a89
    28 N9409cb9dc73d48edadf2440f02cdad6e
    29 schema:publisher N1f47c2fce57040e58eee47df99bab0a4
    30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040769956
    31 https://doi.org/10.1007/978-3-642-27308-7_44
    32 schema:sdDatePublished 2019-04-15T13:30
    33 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    34 schema:sdPublisher N76cfaaa8e7d54f6bae9a5d329f57e180
    35 schema:url http://link.springer.com/10.1007/978-3-642-27308-7_44
    36 sgo:license sg:explorer/license/
    37 sgo:sdDataset chapters
    38 rdf:type schema:Chapter
    39 N06283689527d4d149d3d0cc12a04c438 schema:isbn 978-3-642-27307-0
    40 978-3-642-27308-7
    41 schema:name Advances in Computer Science and Information Technology. Computer Science and Engineering
    42 rdf:type schema:Book
    43 N0d71745137734496acc75ef6254d6d3d schema:affiliation https://www.grid.ac/institutes/grid.45982.32
    44 schema:familyName Das
    45 schema:givenName Devayon
    46 rdf:type schema:Person
    47 N197e3a9a500849b7b57ee9951203c698 rdf:first Nf60d2b9b28e04ee98a3f7aff23296485
    48 rdf:rest N9b6045efdc6d418f80b2e18362be8e59
    49 N1f47c2fce57040e58eee47df99bab0a4 schema:location Berlin, Heidelberg
    50 schema:name Springer Berlin Heidelberg
    51 rdf:type schema:Organisation
    52 N21506b97ca0844e0afed6dda48a4101c schema:name doi
    53 schema:value 10.1007/978-3-642-27308-7_44
    54 rdf:type schema:PropertyValue
    55 N61884f62f30143efb18656a60ae66a89 schema:name dimensions_id
    56 schema:value pub.1040769956
    57 rdf:type schema:PropertyValue
    58 N66a07c014af94d209823219ec9abc8a6 schema:familyName Nagamalai
    59 schema:givenName Dhinaharan
    60 rdf:type schema:Person
    61 N7522e152436e402c949db9d44108b1f9 rdf:first N76a2ba128bbf4dcaa16a21fa3e7b583d
    62 rdf:rest N197e3a9a500849b7b57ee9951203c698
    63 N76a2ba128bbf4dcaa16a21fa3e7b583d schema:familyName Meghanathan
    64 schema:givenName Natarajan
    65 rdf:type schema:Person
    66 N76cfaaa8e7d54f6bae9a5d329f57e180 schema:name Springer Nature - SN SciGraph project
    67 rdf:type schema:Organization
    68 N9409cb9dc73d48edadf2440f02cdad6e schema:name readcube_id
    69 schema:value c23615a4ba12ef0c8f9be7051dd41d97a32457eda75569a08cd1db2be942c7cd
    70 rdf:type schema:PropertyValue
    71 N9b6045efdc6d418f80b2e18362be8e59 rdf:first N66a07c014af94d209823219ec9abc8a6
    72 rdf:rest rdf:nil
    73 Nd5d15aa782aa4ed5a396a17b487f2737 rdf:first N0d71745137734496acc75ef6254d6d3d
    74 rdf:rest Nee35627c8f774d2ab87043c523a984a8
    75 Nee35627c8f774d2ab87043c523a984a8 rdf:first sg:person.013176727273.61
    76 rdf:rest rdf:nil
    77 Nf60d2b9b28e04ee98a3f7aff23296485 schema:familyName Chaki
    78 schema:givenName Nabendu
    79 rdf:type schema:Person
    80 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    81 schema:name Information and Computing Sciences
    82 rdf:type schema:DefinedTerm
    83 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    84 schema:name Artificial Intelligence and Image Processing
    85 rdf:type schema:DefinedTerm
    86 sg:person.013176727273.61 schema:affiliation https://www.grid.ac/institutes/grid.45982.32
    87 schema:familyName Bhattacharyya
    88 schema:givenName Dhruba K.
    89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013176727273.61
    90 rdf:type schema:Person
    91 sg:pub.10.1007/11844662_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041922259
    92 https://doi.org/10.1007/11844662_4
    93 rdf:type schema:CreativeWork
    94 sg:pub.10.1007/978-3-642-00887-0_42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047208706
    95 https://doi.org/10.1007/978-3-642-00887-0_42
    96 rdf:type schema:CreativeWork
    97 https://doi.org/10.1109/icde.2007.367856 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093296979
    98 rdf:type schema:CreativeWork
    99 https://doi.org/10.1109/icde.2007.367857 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095743702
    100 rdf:type schema:CreativeWork
    101 https://doi.org/10.1109/ictm.2009.5412903 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094463223
    102 rdf:type schema:CreativeWork
    103 https://doi.org/10.1109/tkde.2009.139 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061662003
    104 rdf:type schema:CreativeWork
    105 https://doi.org/10.1142/s0218488502001648 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062976751
    106 rdf:type schema:CreativeWork
    107 https://doi.org/10.1142/s021848850200165x schema:sameAs https://app.dimensions.ai/details/publication/pub.1062976752
    108 rdf:type schema:CreativeWork
    109 https://doi.org/10.1145/1217299.1217302 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049597398
    110 rdf:type schema:CreativeWork
    111 https://doi.org/10.1145/1749603.1749605 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022201886
    112 rdf:type schema:CreativeWork
    113 https://doi.org/10.3724/sp.j.1016.2008.00574 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071325558
    114 rdf:type schema:CreativeWork
    115 https://doi.org/10.4018/jisp.2008070103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024502091
    116 rdf:type schema:CreativeWork
    117 https://www.grid.ac/institutes/grid.45982.32 schema:alternateName Tezpur University
    118 schema:name Department of Computer Science and Engineering, Tezpur University, 784028, India
    119 rdf:type schema:Organization
     




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


    ...