2018-08-08
AUTHORSJulien Keuffer , Refik Molva , Hervé Chabanne
ABSTRACTOutsourcing machine learning algorithms helps users to deal with large amounts of data without the need to develop the expertise required by these algorithms. Outsourcing however raises severe security issues due to potentially untrusted service providers. Verifiable computing (VC) tackles some of these issues by assuring computational integrity for an outsourced computation. In this paper, we design a VC protocol tailored to verify a sequence of operations for which no existing VC scheme is suitable to achieve realistic performance objective for the entire sequence. We thus suggest a technique to compose several specialized and efficient VC schemes with a general purpose VC protocol, like Parno et al.’s Pinocchio, by integrating the verification of the proofs generated by these specialized schemes as a function that is part of the sequence of operations verified using the general purpose scheme. The resulting scheme achieves the objectives of the general purpose scheme with increased efficiency for the prover. The scheme relies on the underlying cryptographic assumptions of the composed protocols for correctness and soundness. More... »
PAGES152-171
Computer Security
ISBN
978-3-319-99072-9
978-3-319-99073-6
http://scigraph.springernature.com/pub.10.1007/978-3-319-99073-6_8
DOIhttp://dx.doi.org/10.1007/978-3-319-99073-6_8
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1106097278
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/2008/0802",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Computation Theory and Mathematics",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Eurecom, Biot, France",
"id": "http://www.grid.ac/institutes/grid.28848.3e",
"name": [
"Idemia, Issy-les-Moulineaux, France",
"Eurecom, Biot, France"
],
"type": "Organization"
},
"familyName": "Keuffer",
"givenName": "Julien",
"id": "sg:person.016007512540.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016007512540.26"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Eurecom, Biot, France",
"id": "http://www.grid.ac/institutes/grid.28848.3e",
"name": [
"Eurecom, Biot, France"
],
"type": "Organization"
},
"familyName": "Molva",
"givenName": "Refik",
"id": "sg:person.015760300237.27",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015760300237.27"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Telecom ParisTech, Paris, France",
"id": "http://www.grid.ac/institutes/grid.463717.0",
"name": [
"Idemia, Issy-les-Moulineaux, France",
"Telecom ParisTech, Paris, France"
],
"type": "Organization"
},
"familyName": "Chabanne",
"givenName": "Herv\u00e9",
"id": "sg:person.015205413777.51",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015205413777.51"
],
"type": "Person"
}
],
"datePublished": "2018-08-08",
"datePublishedReg": "2018-08-08",
"description": "Outsourcing machine learning algorithms helps users to deal with large amounts of data without the need to develop the expertise required by these algorithms. Outsourcing however raises severe security issues due to potentially untrusted service providers. Verifiable computing (VC) tackles some of these issues by assuring computational integrity for an outsourced computation. In this paper, we design a VC protocol tailored to verify a sequence of operations for which no existing VC scheme is suitable to achieve realistic performance objective for the entire sequence. We thus suggest a technique to compose several specialized and efficient VC schemes with a general purpose VC protocol, like Parno et al.\u2019s Pinocchio, by integrating the verification of the proofs generated by these specialized schemes as a function that is part of the sequence of operations verified using the general purpose scheme. The resulting scheme achieves the objectives of the general purpose scheme with increased efficiency for the prover. The scheme relies on the underlying cryptographic assumptions of the composed protocols for correctness and soundness.",
"editor": [
{
"familyName": "Lopez",
"givenName": "Javier",
"type": "Person"
},
{
"familyName": "Zhou",
"givenName": "Jianying",
"type": "Person"
},
{
"familyName": "Soriano",
"givenName": "Miguel",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-319-99073-6_8",
"inLanguage": "en",
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-319-99072-9",
"978-3-319-99073-6"
],
"name": "Computer Security",
"type": "Book"
},
"keywords": [
"general-purpose schemes",
"verifiable computing",
"VC scheme",
"sequence of operations",
"untrusted service providers",
"VC protocol",
"severe security issues",
"outsourced computation",
"computational integrity",
"proof composition",
"verifiable computation",
"security issues",
"cryptographic assumptions",
"service providers",
"realistic performance objectives",
"specialized schemes",
"performance objectives",
"algorithm",
"scheme",
"computation",
"large amount",
"computing",
"protocol",
"provers",
"users",
"machine",
"correctness",
"verification",
"operation",
"issues",
"soundness",
"providers",
"Pinocchio",
"proof",
"entire sequence",
"expertise",
"sequence",
"technique",
"efficiency",
"objective",
"need",
"data",
"integrity",
"et al",
"assumption",
"amount",
"part",
"function",
"al",
"composition",
"paper"
],
"name": "Efficient Proof Composition for Verifiable Computation",
"pagination": "152-171",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1106097278"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-319-99073-6_8"
]
}
],
"publisher": {
"name": "Springer Nature",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-319-99073-6_8",
"https://app.dimensions.ai/details/publication/pub.1106097278"
],
"sdDataset": "chapters",
"sdDatePublished": "2022-05-20T07:43",
"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/chapter/chapter_212.jsonl",
"type": "Chapter",
"url": "https://doi.org/10.1007/978-3-319-99073-6_8"
}
]
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.10.1007/978-3-319-99073-6_8'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-99073-6_8'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-99073-6_8'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-99073-6_8'
This table displays all metadata directly associated to this object as RDF triples.
140 TRIPLES
23 PREDICATES
76 URIs
69 LITERALS
7 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/978-3-319-99073-6_8 | schema:about | anzsrc-for:08 |
2 | ″ | ″ | anzsrc-for:0802 |
3 | ″ | schema:author | Nb41aae434a334f8e8f0b321f171f3caf |
4 | ″ | schema:datePublished | 2018-08-08 |
5 | ″ | schema:datePublishedReg | 2018-08-08 |
6 | ″ | schema:description | Outsourcing machine learning algorithms helps users to deal with large amounts of data without the need to develop the expertise required by these algorithms. Outsourcing however raises severe security issues due to potentially untrusted service providers. Verifiable computing (VC) tackles some of these issues by assuring computational integrity for an outsourced computation. In this paper, we design a VC protocol tailored to verify a sequence of operations for which no existing VC scheme is suitable to achieve realistic performance objective for the entire sequence. We thus suggest a technique to compose several specialized and efficient VC schemes with a general purpose VC protocol, like Parno et al.’s Pinocchio, by integrating the verification of the proofs generated by these specialized schemes as a function that is part of the sequence of operations verified using the general purpose scheme. The resulting scheme achieves the objectives of the general purpose scheme with increased efficiency for the prover. The scheme relies on the underlying cryptographic assumptions of the composed protocols for correctness and soundness. |
7 | ″ | schema:editor | Nd83ad0115dd64e5088e97d462e7b94a1 |
8 | ″ | schema:genre | chapter |
9 | ″ | schema:inLanguage | en |
10 | ″ | schema:isAccessibleForFree | false |
11 | ″ | schema:isPartOf | Ndc91aee3913f4b668cacdca6858901ca |
12 | ″ | schema:keywords | Pinocchio |
13 | ″ | ″ | VC protocol |
14 | ″ | ″ | VC scheme |
15 | ″ | ″ | al |
16 | ″ | ″ | algorithm |
17 | ″ | ″ | amount |
18 | ″ | ″ | assumption |
19 | ″ | ″ | composition |
20 | ″ | ″ | computation |
21 | ″ | ″ | computational integrity |
22 | ″ | ″ | computing |
23 | ″ | ″ | correctness |
24 | ″ | ″ | cryptographic assumptions |
25 | ″ | ″ | data |
26 | ″ | ″ | efficiency |
27 | ″ | ″ | entire sequence |
28 | ″ | ″ | et al |
29 | ″ | ″ | expertise |
30 | ″ | ″ | function |
31 | ″ | ″ | general-purpose schemes |
32 | ″ | ″ | integrity |
33 | ″ | ″ | issues |
34 | ″ | ″ | large amount |
35 | ″ | ″ | machine |
36 | ″ | ″ | need |
37 | ″ | ″ | objective |
38 | ″ | ″ | operation |
39 | ″ | ″ | outsourced computation |
40 | ″ | ″ | paper |
41 | ″ | ″ | part |
42 | ″ | ″ | performance objectives |
43 | ″ | ″ | proof |
44 | ″ | ″ | proof composition |
45 | ″ | ″ | protocol |
46 | ″ | ″ | provers |
47 | ″ | ″ | providers |
48 | ″ | ″ | realistic performance objectives |
49 | ″ | ″ | scheme |
50 | ″ | ″ | security issues |
51 | ″ | ″ | sequence |
52 | ″ | ″ | sequence of operations |
53 | ″ | ″ | service providers |
54 | ″ | ″ | severe security issues |
55 | ″ | ″ | soundness |
56 | ″ | ″ | specialized schemes |
57 | ″ | ″ | technique |
58 | ″ | ″ | untrusted service providers |
59 | ″ | ″ | users |
60 | ″ | ″ | verifiable computation |
61 | ″ | ″ | verifiable computing |
62 | ″ | ″ | verification |
63 | ″ | schema:name | Efficient Proof Composition for Verifiable Computation |
64 | ″ | schema:pagination | 152-171 |
65 | ″ | schema:productId | N71b12ce2ffea46feb6a94b3ccb60fa49 |
66 | ″ | ″ | Ndaa8c6315cdb47b187867a35d68a0f71 |
67 | ″ | schema:publisher | N1eef769c7ea144b3a05423e151c8581d |
68 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1106097278 |
69 | ″ | ″ | https://doi.org/10.1007/978-3-319-99073-6_8 |
70 | ″ | schema:sdDatePublished | 2022-05-20T07:43 |
71 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
72 | ″ | schema:sdPublisher | N5358580557bf4ef0809f7f5ca7f3ac55 |
73 | ″ | schema:url | https://doi.org/10.1007/978-3-319-99073-6_8 |
74 | ″ | sgo:license | sg:explorer/license/ |
75 | ″ | sgo:sdDataset | chapters |
76 | ″ | rdf:type | schema:Chapter |
77 | N0435ac8e1a9443be81950f567c614292 | rdf:first | N851573084dd448cf9f556ec7d658a558 |
78 | ″ | rdf:rest | Ne139c54ea5eb487eb52b85db7896f5d4 |
79 | N1d1f49bbf6954b1a8a12754e209d257d | schema:familyName | Soriano |
80 | ″ | schema:givenName | Miguel |
81 | ″ | rdf:type | schema:Person |
82 | N1eef769c7ea144b3a05423e151c8581d | schema:name | Springer Nature |
83 | ″ | rdf:type | schema:Organisation |
84 | N5358580557bf4ef0809f7f5ca7f3ac55 | schema:name | Springer Nature - SN SciGraph project |
85 | ″ | rdf:type | schema:Organization |
86 | N5ba7538b89d24d119f0a8d17517e1c3b | rdf:first | sg:person.015760300237.27 |
87 | ″ | rdf:rest | N7c7877559d524aa781aa326fab60dc05 |
88 | N71b12ce2ffea46feb6a94b3ccb60fa49 | schema:name | doi |
89 | ″ | schema:value | 10.1007/978-3-319-99073-6_8 |
90 | ″ | rdf:type | schema:PropertyValue |
91 | N7c7877559d524aa781aa326fab60dc05 | rdf:first | sg:person.015205413777.51 |
92 | ″ | rdf:rest | rdf:nil |
93 | N851573084dd448cf9f556ec7d658a558 | schema:familyName | Zhou |
94 | ″ | schema:givenName | Jianying |
95 | ″ | rdf:type | schema:Person |
96 | Nb41aae434a334f8e8f0b321f171f3caf | rdf:first | sg:person.016007512540.26 |
97 | ″ | rdf:rest | N5ba7538b89d24d119f0a8d17517e1c3b |
98 | Nb9e1b54170eb4314a350a07f4107c824 | schema:familyName | Lopez |
99 | ″ | schema:givenName | Javier |
100 | ″ | rdf:type | schema:Person |
101 | Nd83ad0115dd64e5088e97d462e7b94a1 | rdf:first | Nb9e1b54170eb4314a350a07f4107c824 |
102 | ″ | rdf:rest | N0435ac8e1a9443be81950f567c614292 |
103 | Ndaa8c6315cdb47b187867a35d68a0f71 | schema:name | dimensions_id |
104 | ″ | schema:value | pub.1106097278 |
105 | ″ | rdf:type | schema:PropertyValue |
106 | Ndc91aee3913f4b668cacdca6858901ca | schema:isbn | 978-3-319-99072-9 |
107 | ″ | ″ | 978-3-319-99073-6 |
108 | ″ | schema:name | Computer Security |
109 | ″ | rdf:type | schema:Book |
110 | Ne139c54ea5eb487eb52b85db7896f5d4 | rdf:first | N1d1f49bbf6954b1a8a12754e209d257d |
111 | ″ | rdf:rest | rdf:nil |
112 | anzsrc-for:08 | schema:inDefinedTermSet | anzsrc-for: |
113 | ″ | schema:name | Information and Computing Sciences |
114 | ″ | rdf:type | schema:DefinedTerm |
115 | anzsrc-for:0802 | schema:inDefinedTermSet | anzsrc-for: |
116 | ″ | schema:name | Computation Theory and Mathematics |
117 | ″ | rdf:type | schema:DefinedTerm |
118 | sg:person.015205413777.51 | schema:affiliation | grid-institutes:grid.463717.0 |
119 | ″ | schema:familyName | Chabanne |
120 | ″ | schema:givenName | Hervé |
121 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015205413777.51 |
122 | ″ | rdf:type | schema:Person |
123 | sg:person.015760300237.27 | schema:affiliation | grid-institutes:grid.28848.3e |
124 | ″ | schema:familyName | Molva |
125 | ″ | schema:givenName | Refik |
126 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015760300237.27 |
127 | ″ | rdf:type | schema:Person |
128 | sg:person.016007512540.26 | schema:affiliation | grid-institutes:grid.28848.3e |
129 | ″ | schema:familyName | Keuffer |
130 | ″ | schema:givenName | Julien |
131 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016007512540.26 |
132 | ″ | rdf:type | schema:Person |
133 | grid-institutes:grid.28848.3e | schema:alternateName | Eurecom, Biot, France |
134 | ″ | schema:name | Eurecom, Biot, France |
135 | ″ | ″ | Idemia, Issy-les-Moulineaux, France |
136 | ″ | rdf:type | schema:Organization |
137 | grid-institutes:grid.463717.0 | schema:alternateName | Telecom ParisTech, Paris, France |
138 | ″ | schema:name | Idemia, Issy-les-Moulineaux, France |
139 | ″ | ″ | Telecom ParisTech, Paris, France |
140 | ″ | rdf:type | schema:Organization |