Ontology type: schema:ScholarlyArticle Open Access: True
2004-10-28
AUTHORSYann Bodo, Nathalie Laurent, Christophe Laurent, Jean-Luc Dugelay
ABSTRACTWith the popularity of high-bandwidth modems and peer-to-peer networks, the contents of videos must be highly protected from piracy. Traditionally, the models utilized to protect this kind of content are scrambling and watermarking. While the former protects the content against eavesdropping (a priori protection), the latter aims at providing a protection against illegal mass distribution (a posteriori protection). Today, researchers agree that both models must be used conjointly to reach a sufficient level of security. However, scrambling works generally by encryption resulting in an unintelligible content for the end-user. At the moment, some applications (such as e-commerce) may require a slight degradation of content so that the user has an idea of the content before buying it. In this paper, we propose a new video protection model, called waterscrambling, whose aim is to give such a quality degradation-based security model. This model works in the compressed domain and disturbs the motion vectors, degrading the video quality. It also allows embedding of a classical invisible watermark enabling protection against mass distribution. In fact, our model can be seen as an intermediary solution to scrambling and watermarking. More... »
PAGES298318
http://scigraph.springernature.com/pub.10.1155/s1110865704401061
DOIhttp://dx.doi.org/10.1155/s1110865704401061
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1063207962
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"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0804",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Data Format",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson S\u00e9vign\u00e9 Cedex, France",
"id": "http://www.grid.ac/institutes/grid.89485.38",
"name": [
"TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson S\u00e9vign\u00e9 Cedex, France"
],
"type": "Organization"
},
"familyName": "Bodo",
"givenName": "Yann",
"id": "sg:person.015145046273.12",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015145046273.12"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson S\u00e9vign\u00e9 Cedex, France",
"id": "http://www.grid.ac/institutes/grid.89485.38",
"name": [
"TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson S\u00e9vign\u00e9 Cedex, France"
],
"type": "Organization"
},
"familyName": "Laurent",
"givenName": "Nathalie",
"id": "sg:person.015646524465.70",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015646524465.70"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson S\u00e9vign\u00e9 Cedex, France",
"id": "http://www.grid.ac/institutes/grid.89485.38",
"name": [
"TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson S\u00e9vign\u00e9 Cedex, France"
],
"type": "Organization"
},
"familyName": "Laurent",
"givenName": "Christophe",
"id": "sg:person.016562547227.02",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016562547227.02"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Multimedia Communication Department, Institut EURECOM, 2229 Route des Cretes, BP 193, 06904, Sophia-Antipolis Cedex, France",
"id": "http://www.grid.ac/institutes/grid.28848.3e",
"name": [
"Multimedia Communication Department, Institut EURECOM, 2229 Route des Cretes, BP 193, 06904, Sophia-Antipolis Cedex, France"
],
"type": "Organization"
},
"familyName": "Dugelay",
"givenName": "Jean-Luc",
"id": "sg:person.015053427343.37",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015053427343.37"
],
"type": "Person"
}
],
"datePublished": "2004-10-28",
"datePublishedReg": "2004-10-28",
"description": "With the popularity of high-bandwidth modems and peer-to-peer networks, the contents of videos must be highly protected from piracy. Traditionally, the models utilized to protect this kind of content are scrambling and watermarking. While the former protects the content against eavesdropping (a priori protection), the latter aims at providing a protection against illegal mass distribution (a posteriori protection). Today, researchers agree that both models must be used conjointly to reach a sufficient level of security. However, scrambling works generally by encryption resulting in an unintelligible content for the end-user. At the moment, some applications (such as e-commerce) may require a slight degradation of content so that the user has an idea of the content before buying it. In this paper, we propose a new video protection model, called waterscrambling, whose aim is to give such a quality degradation-based security model. This model works in the compressed domain and disturbs the motion vectors, degrading the video quality. It also allows embedding of a classical invisible watermark enabling protection against mass distribution. In fact, our model can be seen as an intermediary solution to scrambling and watermarking.",
"genre": "article",
"id": "sg:pub.10.1155/s1110865704401061",
"inLanguage": "en",
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1371279",
"issn": [
"1687-6172",
"1687-0433"
],
"name": "EURASIP Journal on Advances in Signal Processing",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "14",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "2004"
}
],
"keywords": [
"motion vectors",
"content of videos",
"security model",
"kind of content",
"video quality",
"invisible watermark",
"peer networks",
"protection model",
"protection scheme",
"encryption",
"watermark",
"intermediary solution",
"slight degradation",
"video",
"users",
"eavesdropping",
"security",
"modem",
"network",
"embedding",
"popularity",
"piracy",
"scheme",
"model",
"vector",
"peers",
"sufficient level",
"applications",
"researchers",
"idea",
"domain",
"today",
"kind",
"solution",
"quality",
"protection",
"content",
"fact",
"distribution",
"moment",
"levels",
"aim",
"disturbances",
"degradation",
"mass distribution",
"paper"
],
"name": "Video Waterscrambling: Towards a Video Protection Scheme Based on the Disturbance of Motion Vectors",
"pagination": "298318",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1063207962"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1155/s1110865704401061"
]
}
],
"sameAs": [
"https://doi.org/10.1155/s1110865704401061",
"https://app.dimensions.ai/details/publication/pub.1063207962"
],
"sdDataset": "articles",
"sdDatePublished": "2022-05-20T07:22",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_378.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1155/s1110865704401061"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1155/s1110865704401061'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1155/s1110865704401061'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1155/s1110865704401061'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1155/s1110865704401061'
This table displays all metadata directly associated to this object as RDF triples.
132 TRIPLES
21 PREDICATES
72 URIs
63 LITERALS
6 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1155/s1110865704401061 | schema:about | anzsrc-for:08 |
2 | ″ | ″ | anzsrc-for:0801 |
3 | ″ | ″ | anzsrc-for:0804 |
4 | ″ | schema:author | Nf8f49628c7054ed09f661cdd076c78cd |
5 | ″ | schema:datePublished | 2004-10-28 |
6 | ″ | schema:datePublishedReg | 2004-10-28 |
7 | ″ | schema:description | With the popularity of high-bandwidth modems and peer-to-peer networks, the contents of videos must be highly protected from piracy. Traditionally, the models utilized to protect this kind of content are scrambling and watermarking. While the former protects the content against eavesdropping (a priori protection), the latter aims at providing a protection against illegal mass distribution (a posteriori protection). Today, researchers agree that both models must be used conjointly to reach a sufficient level of security. However, scrambling works generally by encryption resulting in an unintelligible content for the end-user. At the moment, some applications (such as e-commerce) may require a slight degradation of content so that the user has an idea of the content before buying it. In this paper, we propose a new video protection model, called waterscrambling, whose aim is to give such a quality degradation-based security model. This model works in the compressed domain and disturbs the motion vectors, degrading the video quality. It also allows embedding of a classical invisible watermark enabling protection against mass distribution. In fact, our model can be seen as an intermediary solution to scrambling and watermarking. |
8 | ″ | schema:genre | article |
9 | ″ | schema:inLanguage | en |
10 | ″ | schema:isAccessibleForFree | true |
11 | ″ | schema:isPartOf | N8bda7db11e9b4d34bc3b4ac1c16dbb4e |
12 | ″ | ″ | Ncecd3903ceb744f49cb02ddf6c5a7ff3 |
13 | ″ | ″ | sg:journal.1371279 |
14 | ″ | schema:keywords | aim |
15 | ″ | ″ | applications |
16 | ″ | ″ | content |
17 | ″ | ″ | content of videos |
18 | ″ | ″ | degradation |
19 | ″ | ″ | distribution |
20 | ″ | ″ | disturbances |
21 | ″ | ″ | domain |
22 | ″ | ″ | eavesdropping |
23 | ″ | ″ | embedding |
24 | ″ | ″ | encryption |
25 | ″ | ″ | fact |
26 | ″ | ″ | idea |
27 | ″ | ″ | intermediary solution |
28 | ″ | ″ | invisible watermark |
29 | ″ | ″ | kind |
30 | ″ | ″ | kind of content |
31 | ″ | ″ | levels |
32 | ″ | ″ | mass distribution |
33 | ″ | ″ | model |
34 | ″ | ″ | modem |
35 | ″ | ″ | moment |
36 | ″ | ″ | motion vectors |
37 | ″ | ″ | network |
38 | ″ | ″ | paper |
39 | ″ | ″ | peer networks |
40 | ″ | ″ | peers |
41 | ″ | ″ | piracy |
42 | ″ | ″ | popularity |
43 | ″ | ″ | protection |
44 | ″ | ″ | protection model |
45 | ″ | ″ | protection scheme |
46 | ″ | ″ | quality |
47 | ″ | ″ | researchers |
48 | ″ | ″ | scheme |
49 | ″ | ″ | security |
50 | ″ | ″ | security model |
51 | ″ | ″ | slight degradation |
52 | ″ | ″ | solution |
53 | ″ | ″ | sufficient level |
54 | ″ | ″ | today |
55 | ″ | ″ | users |
56 | ″ | ″ | vector |
57 | ″ | ″ | video |
58 | ″ | ″ | video quality |
59 | ″ | ″ | watermark |
60 | ″ | schema:name | Video Waterscrambling: Towards a Video Protection Scheme Based on the Disturbance of Motion Vectors |
61 | ″ | schema:pagination | 298318 |
62 | ″ | schema:productId | N95336be7981a46c0b2bacc249682a64d |
63 | ″ | ″ | Nc964ebfe4dbd42a3af4e4ecd8555b4e7 |
64 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1063207962 |
65 | ″ | ″ | https://doi.org/10.1155/s1110865704401061 |
66 | ″ | schema:sdDatePublished | 2022-05-20T07:22 |
67 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
68 | ″ | schema:sdPublisher | N468ad12ea1144632a4b0ebe655c5d8ca |
69 | ″ | schema:url | https://doi.org/10.1155/s1110865704401061 |
70 | ″ | sgo:license | sg:explorer/license/ |
71 | ″ | sgo:sdDataset | articles |
72 | ″ | rdf:type | schema:ScholarlyArticle |
73 | N30eeb0662d9d41c19a2cc72db6f21f0a | rdf:first | sg:person.015646524465.70 |
74 | ″ | rdf:rest | Nf7330630ce3640c1b690218d35fbc86f |
75 | N468ad12ea1144632a4b0ebe655c5d8ca | schema:name | Springer Nature - SN SciGraph project |
76 | ″ | rdf:type | schema:Organization |
77 | N8bda7db11e9b4d34bc3b4ac1c16dbb4e | schema:volumeNumber | 2004 |
78 | ″ | rdf:type | schema:PublicationVolume |
79 | N95336be7981a46c0b2bacc249682a64d | schema:name | dimensions_id |
80 | ″ | schema:value | pub.1063207962 |
81 | ″ | rdf:type | schema:PropertyValue |
82 | N9aef0563768843cb8bf8e3d2d23ce545 | rdf:first | sg:person.015053427343.37 |
83 | ″ | rdf:rest | rdf:nil |
84 | Nc964ebfe4dbd42a3af4e4ecd8555b4e7 | schema:name | doi |
85 | ″ | schema:value | 10.1155/s1110865704401061 |
86 | ″ | rdf:type | schema:PropertyValue |
87 | Ncecd3903ceb744f49cb02ddf6c5a7ff3 | schema:issueNumber | 14 |
88 | ″ | rdf:type | schema:PublicationIssue |
89 | Nf7330630ce3640c1b690218d35fbc86f | rdf:first | sg:person.016562547227.02 |
90 | ″ | rdf:rest | N9aef0563768843cb8bf8e3d2d23ce545 |
91 | Nf8f49628c7054ed09f661cdd076c78cd | rdf:first | sg:person.015145046273.12 |
92 | ″ | rdf:rest | N30eeb0662d9d41c19a2cc72db6f21f0a |
93 | anzsrc-for:08 | schema:inDefinedTermSet | anzsrc-for: |
94 | ″ | schema:name | Information and Computing Sciences |
95 | ″ | rdf:type | schema:DefinedTerm |
96 | anzsrc-for:0801 | schema:inDefinedTermSet | anzsrc-for: |
97 | ″ | schema:name | Artificial Intelligence and Image Processing |
98 | ″ | rdf:type | schema:DefinedTerm |
99 | anzsrc-for:0804 | schema:inDefinedTermSet | anzsrc-for: |
100 | ″ | schema:name | Data Format |
101 | ″ | rdf:type | schema:DefinedTerm |
102 | sg:journal.1371279 | schema:issn | 1687-0433 |
103 | ″ | ″ | 1687-6172 |
104 | ″ | schema:name | EURASIP Journal on Advances in Signal Processing |
105 | ″ | schema:publisher | Springer Nature |
106 | ″ | rdf:type | schema:Periodical |
107 | sg:person.015053427343.37 | schema:affiliation | grid-institutes:grid.28848.3e |
108 | ″ | schema:familyName | Dugelay |
109 | ″ | schema:givenName | Jean-Luc |
110 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015053427343.37 |
111 | ″ | rdf:type | schema:Person |
112 | sg:person.015145046273.12 | schema:affiliation | grid-institutes:grid.89485.38 |
113 | ″ | schema:familyName | Bodo |
114 | ″ | schema:givenName | Yann |
115 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015145046273.12 |
116 | ″ | rdf:type | schema:Person |
117 | sg:person.015646524465.70 | schema:affiliation | grid-institutes:grid.89485.38 |
118 | ″ | schema:familyName | Laurent |
119 | ″ | schema:givenName | Nathalie |
120 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015646524465.70 |
121 | ″ | rdf:type | schema:Person |
122 | sg:person.016562547227.02 | schema:affiliation | grid-institutes:grid.89485.38 |
123 | ″ | schema:familyName | Laurent |
124 | ″ | schema:givenName | Christophe |
125 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016562547227.02 |
126 | ″ | rdf:type | schema:Person |
127 | grid-institutes:grid.28848.3e | schema:alternateName | Multimedia Communication Department, Institut EURECOM, 2229 Route des Cretes, BP 193, 06904, Sophia-Antipolis Cedex, France |
128 | ″ | schema:name | Multimedia Communication Department, Institut EURECOM, 2229 Route des Cretes, BP 193, 06904, Sophia-Antipolis Cedex, France |
129 | ″ | rdf:type | schema:Organization |
130 | grid-institutes:grid.89485.38 | schema:alternateName | TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson Sévigné Cedex, France |
131 | ″ | schema:name | TECH/IRIS/CIM, France Telecom R&D, 4 rue du Clos Courtel, 35512, Cesson Sévigné Cedex, France |
132 | ″ | rdf:type | schema:Organization |