2008-2014
FUNDING AMOUNT400000.0 USD
ABSTRACTThe ubiquity of collections of personal and sensitive data (census surveys, online social networks, and public health data, to name a few) has created a host of new problems stemming from conflicts between data access and privacy. An important challenge for these collections is to discover and release global characteristics of the database without compromising the privacy of the individuals whose data they contain. The problem has been studied extensively in such diverse fields as statistics, databases and data mining. However, the approaches proposed in the literature, until very recently, had either no formal privacy guarantees or ensured security only against limited types of attacks. This project seeks to lay a firm conceptual foundation for the field of privacy in statistical databases, taking into account realistic, sophisticated adversarial attacks and bringing together ideas from several different sub-disciplines of statistics and computer science. The research is centered around three themes: (1) formulating realistic models and definitions of privacy that provide resistance against strong, even active, attacks; (2) understanding the types of information that can, and cannot, be revealed while retaining privacy according to the definitions discussed above; (3) investigating techniques which "break" anonymization protocols, in order to inform protocol design in the same way that cryptanalysis informs modern cryptography. The research is closely tied to questions of resilience and robustness in machine learning and statistics. To ensure the broader impact of the research, this project includes a program of educational and outreach activities including new course development and workshop organization. More... »
URLhttp://www.nsf.gov/awardsearch/showAward?AWD_ID=0747294&HistoricalAwards=false
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/",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"type": "DefinedTerm"
}
],
"amount": {
"currency": "USD",
"type": "MonetaryAmount",
"value": 400000.0
},
"description": "The ubiquity of collections of personal and sensitive data (census surveys, online social networks, and public health data, to name a few) has created a host of new problems stemming from conflicts between data access and privacy. An important challenge for these collections is to discover and release global characteristics of the database without compromising the privacy of the individuals whose data they contain. The problem has been studied extensively in such diverse fields as statistics, databases and data mining. However, the approaches proposed in the literature, until very recently, had either no formal privacy guarantees or ensured security only against limited types of attacks. This project seeks to lay a firm conceptual foundation for the field of privacy in statistical databases, taking into account realistic, sophisticated adversarial attacks and bringing together ideas from several different sub-disciplines of statistics and computer science. The research is centered around three themes: (1) formulating realistic models and definitions of privacy that provide resistance against strong, even active, attacks; (2) understanding the types of information that can, and cannot, be revealed while retaining privacy according to the definitions discussed above; (3) investigating techniques which \"break\" anonymization protocols, in order to inform protocol design in the same way that cryptanalysis informs modern cryptography. The research is closely tied to questions of resilience and robustness in machine learning and statistics. To ensure the broader impact of the research, this project includes a program of educational and outreach activities including new course development and workshop organization.",
"endDate": "2014-08-31",
"funder": {
"id": "http://www.grid.ac/institutes/grid.457785.c",
"type": "Organization"
},
"id": "sg:grant.3084991",
"identifier": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"grant.3084991"
]
},
{
"name": "nsf_id",
"type": "PropertyValue",
"value": [
"0747294"
]
}
],
"keywords": [
"formal privacy guarantees",
"definition of privacy",
"field of privacy",
"anonymization protocol",
"privacy guarantees",
"sensitive data",
"data privacy",
"data mining",
"data access",
"adversarial attacks",
"modern cryptography",
"machine learning",
"computer science",
"privacy",
"protocol design",
"statistical databases",
"type of information",
"firm conceptual foundation",
"new problems",
"attacks",
"important challenge",
"limited types",
"rigorous foundation",
"database",
"global characteristics",
"diverse fields",
"cryptography",
"mining",
"cryptanalysis",
"such diverse fields",
"security",
"guarantees",
"learning",
"conceptual foundations",
"collection",
"project",
"realistic model",
"robustness",
"course development",
"information",
"ubiquity",
"workshop organization",
"access",
"research",
"protocol",
"definition",
"data",
"foundation",
"challenges",
"statistics",
"idea",
"design",
"new course development",
"technique",
"same way",
"questions of resilience",
"broad impact",
"way",
"field",
"organization",
"model",
"order",
"outreach activities",
"science",
"resilience",
"program",
"types",
"development",
"account",
"literature",
"characteristics",
"questions",
"conflict",
"impact",
"host",
"themes",
"individuals",
"activity",
"breaks",
"problem",
"approach",
"resistance"
],
"name": "CAREER: Rigorous Foundations for Data Privacy",
"recipient": [
{
"id": "http://www.grid.ac/institutes/grid.29857.31",
"type": "Organization"
},
{
"affiliation": {
"id": "http://www.grid.ac/institutes/None",
"name": "Pennsylvania State Univ University Park",
"type": "Organization"
},
"familyName": "Smith",
"givenName": "Adam",
"id": "sg:person.013307226666.21",
"type": "Person"
},
{
"member": "sg:person.013307226666.21",
"roleName": "PI",
"type": "Role"
}
],
"sameAs": [
"https://app.dimensions.ai/details/grant/grant.3084991"
],
"sdDataset": "grants",
"sdDatePublished": "2022-08-04T17:24",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/grant/grant_61.jsonl",
"startDate": "2008-09-01",
"type": "MonetaryGrant",
"url": "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0747294&HistoricalAwards=false"
}
]
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/grant.3084991'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/grant.3084991'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/grant.3084991'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/grant.3084991'
This table displays all metadata directly associated to this object as RDF triples.
129 TRIPLES
18 PREDICATES
104 URIs
95 LITERALS
5 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:grant.3084991 | schema:about | anzsrc-for:01 |
2 | ″ | ″ | anzsrc-for:08 |
3 | ″ | schema:amount | N208b3566dd414e9a8c5c082cc5f32022 |
4 | ″ | schema:description | The ubiquity of collections of personal and sensitive data (census surveys, online social networks, and public health data, to name a few) has created a host of new problems stemming from conflicts between data access and privacy. An important challenge for these collections is to discover and release global characteristics of the database without compromising the privacy of the individuals whose data they contain. The problem has been studied extensively in such diverse fields as statistics, databases and data mining. However, the approaches proposed in the literature, until very recently, had either no formal privacy guarantees or ensured security only against limited types of attacks. This project seeks to lay a firm conceptual foundation for the field of privacy in statistical databases, taking into account realistic, sophisticated adversarial attacks and bringing together ideas from several different sub-disciplines of statistics and computer science. The research is centered around three themes: (1) formulating realistic models and definitions of privacy that provide resistance against strong, even active, attacks; (2) understanding the types of information that can, and cannot, be revealed while retaining privacy according to the definitions discussed above; (3) investigating techniques which "break" anonymization protocols, in order to inform protocol design in the same way that cryptanalysis informs modern cryptography. The research is closely tied to questions of resilience and robustness in machine learning and statistics. To ensure the broader impact of the research, this project includes a program of educational and outreach activities including new course development and workshop organization. |
5 | ″ | schema:endDate | 2014-08-31 |
6 | ″ | schema:funder | grid-institutes:grid.457785.c |
7 | ″ | schema:identifier | N0fecc5138b384436baae1c53c849bd3b |
8 | ″ | ″ | N18ff74df6da548aba7533b1ece8cdad5 |
9 | ″ | schema:keywords | access |
10 | ″ | ″ | account |
11 | ″ | ″ | activity |
12 | ″ | ″ | adversarial attacks |
13 | ″ | ″ | anonymization protocol |
14 | ″ | ″ | approach |
15 | ″ | ″ | attacks |
16 | ″ | ″ | breaks |
17 | ″ | ″ | broad impact |
18 | ″ | ″ | challenges |
19 | ″ | ″ | characteristics |
20 | ″ | ″ | collection |
21 | ″ | ″ | computer science |
22 | ″ | ″ | conceptual foundations |
23 | ″ | ″ | conflict |
24 | ″ | ″ | course development |
25 | ″ | ″ | cryptanalysis |
26 | ″ | ″ | cryptography |
27 | ″ | ″ | data |
28 | ″ | ″ | data access |
29 | ″ | ″ | data mining |
30 | ″ | ″ | data privacy |
31 | ″ | ″ | database |
32 | ″ | ″ | definition |
33 | ″ | ″ | definition of privacy |
34 | ″ | ″ | design |
35 | ″ | ″ | development |
36 | ″ | ″ | diverse fields |
37 | ″ | ″ | field |
38 | ″ | ″ | field of privacy |
39 | ″ | ″ | firm conceptual foundation |
40 | ″ | ″ | formal privacy guarantees |
41 | ″ | ″ | foundation |
42 | ″ | ″ | global characteristics |
43 | ″ | ″ | guarantees |
44 | ″ | ″ | host |
45 | ″ | ″ | idea |
46 | ″ | ″ | impact |
47 | ″ | ″ | important challenge |
48 | ″ | ″ | individuals |
49 | ″ | ″ | information |
50 | ″ | ″ | learning |
51 | ″ | ″ | limited types |
52 | ″ | ″ | literature |
53 | ″ | ″ | machine learning |
54 | ″ | ″ | mining |
55 | ″ | ″ | model |
56 | ″ | ″ | modern cryptography |
57 | ″ | ″ | new course development |
58 | ″ | ″ | new problems |
59 | ″ | ″ | order |
60 | ″ | ″ | organization |
61 | ″ | ″ | outreach activities |
62 | ″ | ″ | privacy |
63 | ″ | ″ | privacy guarantees |
64 | ″ | ″ | problem |
65 | ″ | ″ | program |
66 | ″ | ″ | project |
67 | ″ | ″ | protocol |
68 | ″ | ″ | protocol design |
69 | ″ | ″ | questions |
70 | ″ | ″ | questions of resilience |
71 | ″ | ″ | realistic model |
72 | ″ | ″ | research |
73 | ″ | ″ | resilience |
74 | ″ | ″ | resistance |
75 | ″ | ″ | rigorous foundation |
76 | ″ | ″ | robustness |
77 | ″ | ″ | same way |
78 | ″ | ″ | science |
79 | ″ | ″ | security |
80 | ″ | ″ | sensitive data |
81 | ″ | ″ | statistical databases |
82 | ″ | ″ | statistics |
83 | ″ | ″ | such diverse fields |
84 | ″ | ″ | technique |
85 | ″ | ″ | themes |
86 | ″ | ″ | type of information |
87 | ″ | ″ | types |
88 | ″ | ″ | ubiquity |
89 | ″ | ″ | way |
90 | ″ | ″ | workshop organization |
91 | ″ | schema:name | CAREER: Rigorous Foundations for Data Privacy |
92 | ″ | schema:recipient | Nef41fc0882b74db2b7c8ed7e2c612d5c |
93 | ″ | ″ | sg:person.013307226666.21 |
94 | ″ | ″ | grid-institutes:grid.29857.31 |
95 | ″ | schema:sameAs | https://app.dimensions.ai/details/grant/grant.3084991 |
96 | ″ | schema:sdDatePublished | 2022-08-04T17:24 |
97 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
98 | ″ | schema:sdPublisher | N7186bcda665842249e334e2d860d737a |
99 | ″ | schema:startDate | 2008-09-01 |
100 | ″ | schema:url | http://www.nsf.gov/awardsearch/showAward?AWD_ID=0747294&HistoricalAwards=false |
101 | ″ | sgo:license | sg:explorer/license/ |
102 | ″ | sgo:sdDataset | grants |
103 | ″ | rdf:type | schema:MonetaryGrant |
104 | N0fecc5138b384436baae1c53c849bd3b | schema:name | dimensions_id |
105 | ″ | schema:value | grant.3084991 |
106 | ″ | rdf:type | schema:PropertyValue |
107 | N18ff74df6da548aba7533b1ece8cdad5 | schema:name | nsf_id |
108 | ″ | schema:value | 0747294 |
109 | ″ | rdf:type | schema:PropertyValue |
110 | N208b3566dd414e9a8c5c082cc5f32022 | schema:currency | USD |
111 | ″ | schema:value | 400000.0 |
112 | ″ | rdf:type | schema:MonetaryAmount |
113 | N7186bcda665842249e334e2d860d737a | schema:name | Springer Nature - SN SciGraph project |
114 | ″ | rdf:type | schema:Organization |
115 | Nef41fc0882b74db2b7c8ed7e2c612d5c | schema:member | sg:person.013307226666.21 |
116 | ″ | schema:roleName | PI |
117 | ″ | rdf:type | schema:Role |
118 | anzsrc-for:01 | schema:inDefinedTermSet | anzsrc-for: |
119 | ″ | rdf:type | schema:DefinedTerm |
120 | anzsrc-for:08 | schema:inDefinedTermSet | anzsrc-for: |
121 | ″ | rdf:type | schema:DefinedTerm |
122 | sg:person.013307226666.21 | schema:affiliation | grid-institutes:None |
123 | ″ | schema:familyName | Smith |
124 | ″ | schema:givenName | Adam |
125 | ″ | rdf:type | schema:Person |
126 | grid-institutes:None | schema:name | Pennsylvania State Univ University Park |
127 | ″ | rdf:type | schema:Organization |
128 | grid-institutes:grid.29857.31 | ″ | schema:Organization |
129 | grid-institutes:grid.457785.c | ″ | schema:Organization |