東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Database anonymization : = privacy m...

Domingo-Ferrer, Josep,

Linked to FindBook

Google Book

Amazon

博客來

Database anonymization : = privacy models, data utility, and microaggregation-based inter-model connections /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Database anonymization :/ Josep Domingo- Ferrer, David Sa?nchez, and Jordi Soria-Comas, Universitat Rovira i Virgili, Tarragona, Catalonia
Reminder of title:	privacy models, data utility, and microaggregation-based inter-model connections /
Author:	Domingo-Ferrer, Josep,
other author:	Sa?nchez, David
Description:	1 online resource (xv, 120 pages) :illustrations
[NT 15003449]:	1. Introduction
[NT 15003449]:	2. Privacy in data releases -- 2.1 Types of data releases -- 2.2 Microdata sets -- 2.3 Formalizing privacy -- 2.4 Disclosure risk in microdata sets -- 2.5 Microdata anonymization -- 2.6 Measuring information loss -- 2.7 Trading off information loss and disclosure risk -- 2.8 Summary
[NT 15003449]:	3. Anonymization methods for microdata -- 3.1 Non-perturbative masking methods -- 3.2 Perturbative masking methods -- 3.3 Synthetic data generation -- 3.4 Summary
[NT 15003449]:	4. Quantifying disclosure risk: record linkage -- 4.1 Threshold -based record linkage -- 4.2 Rule-based record linkage -- 4.3 Probabilistic record linkage -- 4.4 Summary
[NT 15003449]:	5. The k-anonymity privacy model -- 5.1 Insufficiency of data de-identification -- 5.2 The k-anonymity model -- 5.3 Generalization and suppression based k-anonymity -- 5.4 Microaggregation-based k-anonymity -- 5.5 Probabilistic k- anonymity -- 5.6 Summary
[NT 15003449]:	6. Beyond k-anonymity: l-diversity and t -closeness -- 6.1 l- diversity -- 6.2 t-closeness -- 6.3 Summary
[NT 15003449]:	7. t-closeness through microaggregation -- 7.1 Standard microaggregation and merging -- 7.2 t-closeness aware microaggregation: k-anonymity-first -- 7.3 t-closeness aware microaggregation: t-closeness-first -- 7.4 Summary
[NT 15003449]:	8. Differential privacy -- 8.1 Definition -- 8.2 Calibration to the global sensitivity -- 8.3 Calibration to the smooth sensitivity -- 8.4 The exponential mechanism -- 8.5 Relation to k -anonymity-based models -- 8.6 Differentially private data publishing -- 8.7 Summary
[NT 15003449]:	9. Differential privacy by multivariate microaggregation -- 9.1 Reducing sensitivity via prior multivariate microaggregation -- 9.2 Differentially private data sets by insensitive microaggregation -- 9.3 General insensitive microaggregation -- 9.4 Differential privacy with categorical attributes -- 9.5 A semantic distance for differential privacy -- 9.6 Integrating heterogeneous attribute types -- 9.7 Summary
[NT 15003449]:	10. Differential privacy by individual ranking microaggregation -- 10.1 Limitations of multivariate microaggregation -- 10.2 Sensitivity reduction via individual ranking -- 10.3 Choosing the microggregation parameter k -- 10.4 Summary
[NT 15003449]:	11. Conclusions and research directions -- 11.1 Summary and conclusions -- 11.2 Research directions -- Bibliography -- Authors' biographies
Subject:	Data protection - Congresses. -
Online resource:	http://portal.igpublish.com/iglibrary/search/MCPB0000810.html
ISBN:	9781627058445

Database anonymization : = privacy models, data utility, and microaggregation-based inter-model connections /
Domingo-Ferrer, Josep,

Database anonymization :privacy models, data utility, and microaggregation-based inter-model connections /Josep Domingo- Ferrer, David Sa?nchez, and Jordi Soria-Comas, Universitat Rovira i Virgili, Tarragona, Catalonia - 1 online resource (xv, 120 pages) :illustrations - Synthesis lectures on information security, privacy, & trust, #151945-9750 ;. - Synthesis lectures on information security, privacy and trust ; #15..

Includes bibliographical references (pages 109-118)

1. Introduction

The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature

ISBN: 9781627058445

Standard No.: 10.2200 / S00690ED1V01Y201512SPT015doiSubjects--Topical Terms:

1244180
Data protection
--Congresses.Subjects--Index Terms:

data releasesIndex Terms--Genre/Form:

959526
Electronic books

Dewey Class. No.: 658.478

Database anonymization : = privacy models, data utility, and microaggregation-based inter-model connections /
LDR:05583nmm0a2200529 ib450 001 2139180
005 20181023224339.0
006 m o d
007 cr cnu---unuuu
008 181127s2016 caua fob 000 0 eng d
020 $a 9781627058445 $q (ebook)
020 $a 1627058443 $q (ebook)
020 $z 9781627058438 $q (print)
024 7 $a 10.2200 / S00690ED1V01Y201512SPT015 $2 doi
035 $a IGP290283
040 $a CaBNVSL $b eng $e rda $e pn $c J2I $d J2I $d UIU $d EBLCP $d WAU $d YDXCP $d OCLCA $d NTBC
082 0 4 $a 658.478 $2 23
100 1 $a Domingo-Ferrer, Josep, $e author $3 3314873
245 1 0 $a Database anonymization : $b privacy models, data utility, and microaggregation-based inter-model connections / $c Josep Domingo- Ferrer, David Sa?nchez, and Jordi Soria-Comas, Universitat Rovira i Virgili, Tarragona, Catalonia
264 1 $a San Rafael, California : $b Morgan & Claypool Publishers, $c [2016]
300 $a 1 online resource (xv, 120 pages) : $b illustrations
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
490 0 $a Synthesis lectures on information security, privacy, & trust, $x 1945-9750 ; $v #15
504 $a Includes bibliographical references (pages 109-118)
505 0 $a 1. Introduction
505 8 $a 2. Privacy in data releases -- 2.1 Types of data releases -- 2.2 Microdata sets -- 2.3 Formalizing privacy -- 2.4 Disclosure risk in microdata sets -- 2.5 Microdata anonymization -- 2.6 Measuring information loss -- 2.7 Trading off information loss and disclosure risk -- 2.8 Summary
505 8 $a 3. Anonymization methods for microdata -- 3.1 Non-perturbative masking methods -- 3.2 Perturbative masking methods -- 3.3 Synthetic data generation -- 3.4 Summary
505 8 $a 4. Quantifying disclosure risk: record linkage -- 4.1 Threshold -based record linkage -- 4.2 Rule-based record linkage -- 4.3 Probabilistic record linkage -- 4.4 Summary
505 8 $a 5. The k-anonymity privacy model -- 5.1 Insufficiency of data de-identification -- 5.2 The k-anonymity model -- 5.3 Generalization and suppression based k-anonymity -- 5.4 Microaggregation-based k-anonymity -- 5.5 Probabilistic k- anonymity -- 5.6 Summary
505 8 $a 6. Beyond k-anonymity: l-diversity and t -closeness -- 6.1 l- diversity -- 6.2 t-closeness -- 6.3 Summary
505 8 $a 7. t-closeness through microaggregation -- 7.1 Standard microaggregation and merging -- 7.2 t-closeness aware microaggregation: k-anonymity-first -- 7.3 t-closeness aware microaggregation: t-closeness-first -- 7.4 Summary
505 8 $a 8. Differential privacy -- 8.1 Definition -- 8.2 Calibration to the global sensitivity -- 8.3 Calibration to the smooth sensitivity -- 8.4 The exponential mechanism -- 8.5 Relation to k -anonymity-based models -- 8.6 Differentially private data publishing -- 8.7 Summary
505 8 $a 9. Differential privacy by multivariate microaggregation -- 9.1 Reducing sensitivity via prior multivariate microaggregation -- 9.2 Differentially private data sets by insensitive microaggregation -- 9.3 General insensitive microaggregation -- 9.4 Differential privacy with categorical attributes -- 9.5 A semantic distance for differential privacy -- 9.6 Integrating heterogeneous attribute types -- 9.7 Summary
505 8 $a 10. Differential privacy by individual ranking microaggregation -- 10.1 Limitations of multivariate microaggregation -- 10.2 Sensitivity reduction via individual ranking -- 10.3 Choosing the microggregation parameter k -- 10.4 Summary
505 8 $a 11. Conclusions and research directions -- 11.1 Summary and conclusions -- 11.2 Research directions -- Bibliography -- Authors' biographies
520 $a The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature
520 $a Besides, as a more advanced topic, we identify and discuss in detail connections between several privacy models (i.e., how to accumulate the privacy guarantees they offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization methods can be used to enforce privacy models and thereby offer ex ante privacy guarantees). These latter topics are relevant to researchers and advanced practitioners, who will gain a deeper understanding on the available data anonymization solutions and the privacy guarantees they can offer
588 $a Online resource; title from PDF title page (Morgan & Claypool, viewed on January 22, 2016)
650 0 $a Data protection $v Congresses. $3 1244180
650 0 $a Database security $v Congresses. $3 1244091
653 $a data releases
653 $a privacy protection
653 $a anonymization
653 $a privacy models
653 $a statistical disclosure limitation
653 $a statistical disclosure control
653 $a microaggregation
655 4 $a Electronic books $3 959526
700 1 $a Sa?nchez, David $c (Computer scientist), $e author $3 3314874
700 1 $a Soria-Comas, Jordi, $e author $3 3314875
776 0 8 $i Print version: $z 9781627058438
830 0 $a Synthesis lectures on information security, privacy and trust ; $v #15. $x 1945-9742 $3 3314876
856 4 0 $u http://portal.igpublish.com/iglibrary/search/MCPB0000810.html