Progressive Visual Secret Sharing with Multiple Decryptions and Unexpanded Shares View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015-05-28

AUTHORS

Guohui Chen , Chunying Wang , Xuehu Yan , Peng Li

ABSTRACT

Differently from traditional secret sharing, progressive and perceptual secret sharing can gain clearer recovered secret image with more shares. Recently, Hou and Quan proposed a progressive visual secret sharing (PVSS) scheme that solves the pixel expansion problem of previous research. However, Hou and Quan’s scheme suffers from some problems, such as different color representation from ordinary digital images, and lossy recovery. Aiming to solve the problems, in this paper, one PVSS scheme is proposed, which has the abilities of stacking and additive decryptions. If a light-weight device is not available, the secret could be reconstructed by stacking. On the other hand, if a light-weight device is available, the secret will be reconstructed losslessly by additive operation. In addition, the proposed scheme has no the pixel expansion as well as supports different image formats. Experiments are conducted to evaluate the efficiency of the proposed scheme. More... »

PAGES

376-386

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-19321-2_28

DOI

http://dx.doi.org/10.1007/978-3-319-19321-2_28

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1023489752


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Hebei University of Science and Technology, 050018, Shi Jiazhuang, China", 
          "id": "http://www.grid.ac/institutes/grid.462323.2", 
          "name": [
            "Hebei University of Science and Technology, 050018, Shi Jiazhuang, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chen", 
        "givenName": "Guohui", 
        "id": "sg:person.012634637662.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012634637662.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hebei Sailhero Environmental Protection Hi-teeh Co.Ltd., 050035, Shi Jiazhuang, China", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Hebei Sailhero Environmental Protection Hi-teeh Co.Ltd., 050035, Shi Jiazhuang, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Chunying", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Computer Science and Technology, Harbin Institute of Technology, 150080, Harbin, China", 
          "id": "http://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Computer Science and Technology, Harbin Institute of Technology, 150080, Harbin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yan", 
        "givenName": "Xuehu", 
        "id": "sg:person.010467364517.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010467364517.31"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Mathematics and Physics, North China Electric Power University, 071003, Baoding, China", 
          "id": "http://www.grid.ac/institutes/grid.261049.8", 
          "name": [
            "Department of Mathematics and Physics, North China Electric Power University, 071003, Baoding, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Peng", 
        "type": "Person"
      }
    ], 
    "datePublished": "2015-05-28", 
    "datePublishedReg": "2015-05-28", 
    "description": "Differently from traditional secret sharing, progressive and perceptual secret sharing can gain clearer recovered secret image with more shares. Recently, Hou and Quan proposed a progressive visual secret sharing (PVSS) scheme that solves the pixel expansion problem of previous research. However, Hou and Quan\u2019s scheme suffers from some problems, such as different color representation from ordinary digital images, and lossy recovery. Aiming to solve the problems, in this paper, one PVSS scheme is proposed, which has the abilities of stacking and additive decryptions. If a light-weight device is not available, the secret could be reconstructed by stacking. On the other hand, if a light-weight device is available, the secret will be reconstructed losslessly by additive operation. In addition, the proposed scheme has no the pixel expansion as well as supports different image formats. Experiments are conducted to evaluate the efficiency of the proposed scheme.", 
    "editor": [
      {
        "familyName": "Shi", 
        "givenName": "Yun-Qing", 
        "type": "Person"
      }, 
      {
        "familyName": "Kim", 
        "givenName": "Hyoung Joong", 
        "type": "Person"
      }, 
      {
        "familyName": "P\u00e9rez-Gonz\u00e1lez", 
        "givenName": "Fernando", 
        "type": "Person"
      }, 
      {
        "familyName": "Yang", 
        "givenName": "Ching-Nung", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-19321-2_28", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-19320-5", 
        "978-3-319-19321-2"
      ], 
      "name": "Digital-Forensics and Watermarking", 
      "type": "Book"
    }, 
    "keywords": [
      "secret sharing", 
      "light-weight devices", 
      "visual secret sharing scheme", 
      "Progressive Visual Secret Sharing", 
      "visual secret sharing", 
      "pixel expansion problem", 
      "traditional secret sharing", 
      "secret sharing scheme", 
      "ordinary digital images", 
      "different image formats", 
      "different color representations", 
      "secret image", 
      "lossy recovery", 
      "PVSS scheme", 
      "pixel expansion", 
      "multiple decryptions", 
      "sharing scheme", 
      "image format", 
      "unexpanded shares", 
      "digital images", 
      "additive operations", 
      "decryption", 
      "color representation", 
      "sharing", 
      "more shares", 
      "scheme", 
      "images", 
      "expansion problem", 
      "secrets", 
      "devices", 
      "format", 
      "representation", 
      "previous research", 
      "operation", 
      "efficiency", 
      "share", 
      "experiments", 
      "research", 
      "hand", 
      "Hou", 
      "ability", 
      "Quan", 
      "addition", 
      "expansion", 
      "recovery", 
      "problem", 
      "paper"
    ], 
    "name": "Progressive Visual Secret Sharing with Multiple Decryptions and Unexpanded Shares", 
    "pagination": "376-386", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1023489752"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-19321-2_28"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-19321-2_28", 
      "https://app.dimensions.ai/details/publication/pub.1023489752"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-11-24T21:11", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/chapter/chapter_113.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-319-19321-2_28"
  }
]
 

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.10.1007/978-3-319-19321-2_28'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-19321-2_28'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-19321-2_28'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-19321-2_28'


 

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

149 TRIPLES      22 PREDICATES      71 URIs      64 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-19321-2_28 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N59d0d8fd553546108384b04e10501fe5
4 schema:datePublished 2015-05-28
5 schema:datePublishedReg 2015-05-28
6 schema:description Differently from traditional secret sharing, progressive and perceptual secret sharing can gain clearer recovered secret image with more shares. Recently, Hou and Quan proposed a progressive visual secret sharing (PVSS) scheme that solves the pixel expansion problem of previous research. However, Hou and Quan’s scheme suffers from some problems, such as different color representation from ordinary digital images, and lossy recovery. Aiming to solve the problems, in this paper, one PVSS scheme is proposed, which has the abilities of stacking and additive decryptions. If a light-weight device is not available, the secret could be reconstructed by stacking. On the other hand, if a light-weight device is available, the secret will be reconstructed losslessly by additive operation. In addition, the proposed scheme has no the pixel expansion as well as supports different image formats. Experiments are conducted to evaluate the efficiency of the proposed scheme.
7 schema:editor N9768e072a31547619a45b1c1b0669491
8 schema:genre chapter
9 schema:isAccessibleForFree false
10 schema:isPartOf Nc2a4cc233d3b4a769b4549b4fdd7937e
11 schema:keywords Hou
12 PVSS scheme
13 Progressive Visual Secret Sharing
14 Quan
15 ability
16 addition
17 additive operations
18 color representation
19 decryption
20 devices
21 different color representations
22 different image formats
23 digital images
24 efficiency
25 expansion
26 expansion problem
27 experiments
28 format
29 hand
30 image format
31 images
32 light-weight devices
33 lossy recovery
34 more shares
35 multiple decryptions
36 operation
37 ordinary digital images
38 paper
39 pixel expansion
40 pixel expansion problem
41 previous research
42 problem
43 recovery
44 representation
45 research
46 scheme
47 secret image
48 secret sharing
49 secret sharing scheme
50 secrets
51 share
52 sharing
53 sharing scheme
54 traditional secret sharing
55 unexpanded shares
56 visual secret sharing
57 visual secret sharing scheme
58 schema:name Progressive Visual Secret Sharing with Multiple Decryptions and Unexpanded Shares
59 schema:pagination 376-386
60 schema:productId N5173293839eb4b8498687159eddd68a3
61 Nf9ef6c2a4a5a4aa3a328b1e63d043ace
62 schema:publisher Nfd7d9e8c2e7248f8b70d8b25de5acfbb
63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023489752
64 https://doi.org/10.1007/978-3-319-19321-2_28
65 schema:sdDatePublished 2022-11-24T21:11
66 schema:sdLicense https://scigraph.springernature.com/explorer/license/
67 schema:sdPublisher N0ea751e3f65945d1af7b312c1c22ffc5
68 schema:url https://doi.org/10.1007/978-3-319-19321-2_28
69 sgo:license sg:explorer/license/
70 sgo:sdDataset chapters
71 rdf:type schema:Chapter
72 N0cab7fb5d65647d5a7734ac1d585803b schema:affiliation grid-institutes:None
73 schema:familyName Wang
74 schema:givenName Chunying
75 rdf:type schema:Person
76 N0ea751e3f65945d1af7b312c1c22ffc5 schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 N3ac4af9d34914ebbbbd28169820b17e0 schema:familyName Pérez-González
79 schema:givenName Fernando
80 rdf:type schema:Person
81 N5173293839eb4b8498687159eddd68a3 schema:name doi
82 schema:value 10.1007/978-3-319-19321-2_28
83 rdf:type schema:PropertyValue
84 N58153d5b61994bfbb4bab339e6ae3273 schema:familyName Yang
85 schema:givenName Ching-Nung
86 rdf:type schema:Person
87 N59d0d8fd553546108384b04e10501fe5 rdf:first sg:person.012634637662.53
88 rdf:rest N944d574b46054191961d0fb8b1434f3d
89 N5d389c5021da4aa98dfb61eb3c3d95b7 rdf:first N9f02cc2b6c86462bb459da9fc4654e93
90 rdf:rest Ncb059ef1ea3245e8adffa3af50338621
91 N7c1e2853d749480d979347ded3f114f1 rdf:first N58153d5b61994bfbb4bab339e6ae3273
92 rdf:rest rdf:nil
93 N7f6c5486a9f94e4791a61e8d28910efb rdf:first sg:person.010467364517.31
94 rdf:rest N96d4a43f705c46a686133ddd2a7680c5
95 N944d574b46054191961d0fb8b1434f3d rdf:first N0cab7fb5d65647d5a7734ac1d585803b
96 rdf:rest N7f6c5486a9f94e4791a61e8d28910efb
97 N96d4a43f705c46a686133ddd2a7680c5 rdf:first Nb9cac34d60cc4fe685cde630cc32e73a
98 rdf:rest rdf:nil
99 N9768e072a31547619a45b1c1b0669491 rdf:first Nbb0f6a4ff40a4e44a143af899cc9d3aa
100 rdf:rest N5d389c5021da4aa98dfb61eb3c3d95b7
101 N9f02cc2b6c86462bb459da9fc4654e93 schema:familyName Kim
102 schema:givenName Hyoung Joong
103 rdf:type schema:Person
104 Nb9cac34d60cc4fe685cde630cc32e73a schema:affiliation grid-institutes:grid.261049.8
105 schema:familyName Li
106 schema:givenName Peng
107 rdf:type schema:Person
108 Nbb0f6a4ff40a4e44a143af899cc9d3aa schema:familyName Shi
109 schema:givenName Yun-Qing
110 rdf:type schema:Person
111 Nc2a4cc233d3b4a769b4549b4fdd7937e schema:isbn 978-3-319-19320-5
112 978-3-319-19321-2
113 schema:name Digital-Forensics and Watermarking
114 rdf:type schema:Book
115 Ncb059ef1ea3245e8adffa3af50338621 rdf:first N3ac4af9d34914ebbbbd28169820b17e0
116 rdf:rest N7c1e2853d749480d979347ded3f114f1
117 Nf9ef6c2a4a5a4aa3a328b1e63d043ace schema:name dimensions_id
118 schema:value pub.1023489752
119 rdf:type schema:PropertyValue
120 Nfd7d9e8c2e7248f8b70d8b25de5acfbb schema:name Springer Nature
121 rdf:type schema:Organisation
122 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
123 schema:name Information and Computing Sciences
124 rdf:type schema:DefinedTerm
125 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
126 schema:name Artificial Intelligence and Image Processing
127 rdf:type schema:DefinedTerm
128 sg:person.010467364517.31 schema:affiliation grid-institutes:grid.19373.3f
129 schema:familyName Yan
130 schema:givenName Xuehu
131 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010467364517.31
132 rdf:type schema:Person
133 sg:person.012634637662.53 schema:affiliation grid-institutes:grid.462323.2
134 schema:familyName Chen
135 schema:givenName Guohui
136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012634637662.53
137 rdf:type schema:Person
138 grid-institutes:None schema:alternateName Hebei Sailhero Environmental Protection Hi-teeh Co.Ltd., 050035, Shi Jiazhuang, China
139 schema:name Hebei Sailhero Environmental Protection Hi-teeh Co.Ltd., 050035, Shi Jiazhuang, China
140 rdf:type schema:Organization
141 grid-institutes:grid.19373.3f schema:alternateName School of Computer Science and Technology, Harbin Institute of Technology, 150080, Harbin, China
142 schema:name School of Computer Science and Technology, Harbin Institute of Technology, 150080, Harbin, China
143 rdf:type schema:Organization
144 grid-institutes:grid.261049.8 schema:alternateName Department of Mathematics and Physics, North China Electric Power University, 071003, Baoding, China
145 schema:name Department of Mathematics and Physics, North China Electric Power University, 071003, Baoding, China
146 rdf:type schema:Organization
147 grid-institutes:grid.462323.2 schema:alternateName Hebei University of Science and Technology, 050018, Shi Jiazhuang, China
148 schema:name Hebei University of Science and Technology, 050018, Shi Jiazhuang, China
149 rdf:type schema:Organization
 




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


...