Soft Cover. Condition: Good. Ex-library with the usual features. Library label on front cover. The interior is clean and tight. Binding is good. Cover shows very light wear. Ex-Library.
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Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
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Condition: As New. Unread book in perfect condition.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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Language: English
Published by Springer International Publishing, Springer International Publishing Feb 2010, 2010
ISBN 10: 3031007069 ISBN 13: 9783031007064
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. Neuware -Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical data, sensitive information can be the fact that a particular patient suffers from HIV. In spatial data, sensitive information can be a specific location of an individual. In web surfing data, the information that a user browses certain websites may be considered sensitive. Consider a dataset containing some sensitive information is to be released to the public. In order to protect sensitive information, the simplest solution is not to disclose the information. However, this would be an overkill since it will hinder the process of data analysis over the data from which we can find interesting patterns. Moreover, in some applications, the data must be disclosed under the government regulations. Alternatively, the data owner can first modify the data such that the modified data can guarantee privacy and, at the same time, the modified data retains sufficient utility and can be released to other parties safely. This process is usually called as privacy-preserving data publishing. In this monograph, we study how the data owner can modify the data and how the modified data can preserve privacy and protect sensitive information. Table of Contents: Introduction / Fundamental Concepts / One-Time Data Publishing / Multiple-Time Data Publishing / Graph Data / Other Data Types / Future Research DirectionsSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 140 pp. Englisch.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: California Books, Miami, FL, U.S.A.
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Language: English
Published by Springer International Publishing, 2010
ISBN 10: 3031007069 ISBN 13: 9783031007064
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical data, sensitive information can be the fact that a particular patient suffers from HIV. In spatial data, sensitive information can be a specific location of an individual. In web surfing data, the information that a user browses certain websites may be considered sensitive. Consider a dataset containing some sensitive information is to be released to the public. In order to protect sensitive information, the simplest solution is not to disclose the information. However, this would be an overkill since it will hinder the process of data analysis over the data from which we can find interesting patterns. Moreover, in some applications, the data must be disclosed under the government regulations. Alternatively, the data owner can first modify the data such that the modified data can guarantee privacy and, at the same time, the modified data retains sufficient utility and can be released to other parties safely. This process is usually called as privacy-preserving data publishing. In this monograph, we study how the data owner can modify the data and how the modified data can preserve privacy and protect sensitive information. Table of Contents: Introduction / Fundamental Concepts / One-Time Data Publishing / Multiple-Time Data Publishing / Graph Data / Other Data Types / Future Research Directions.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: Majestic Books, Hounslow, United Kingdom
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Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Chapman and Hall/CRC 2019-09-27, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
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Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st edition NO-PA16APR2015-KAP.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
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Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367383756 ISBN 13: 9780367383756
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Add to basketPaperback. Condition: Brand New. reprint edition. 344 pages. 9.00x6.00x0.75 inches. In Stock.
Language: English
Published by Chapman and Hall/CRC 2010-08-02, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
Seller: Chiron Media, Wallingford, United Kingdom
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Published by Chapman and Hall/CRC, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
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Published by Chapman and Hall/CRC, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: English
Published by Chapman and Hall/CRC, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Language: English
Published by Chapman and Hall/CRC, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Chapman and Hall/CRC, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
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Published by Chapman and Hall/CRC, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
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Published by Taylor & Francis Group, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 376.
Language: English
Published by Taylor & Francis Group, 2010
ISBN 10: 1420091484 ISBN 13: 9781420091489
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. pp. 376.
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketHardcover. Condition: Brand New. 1st edition. 376 pages. 9.50x6.25x1.00 inches. In Stock.
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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Language: English
Published by Springer International Publishing Feb 2010, 2010
ISBN 10: 3031007069 ISBN 13: 9783031007064
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical data, sensitive information can be the fact that a particular patient suffers from HIV. In spatial data, sensitive information can be a specific location of an individual. In web surfing data, the information that a user browses certain websites may be considered sensitive. Consider a dataset containing some sensitive information is to be released to the public. In order to protect sensitive information, the simplest solution is not to disclose the information. However, this would be an overkill since it will hinder the process of data analysis over the data from which we can find interesting patterns. Moreover, in some applications, the data must be disclosed under the government regulations. Alternatively, the data owner can first modify the data such that the modified data can guarantee privacy and, at the same time, the modified data retains sufficient utility and can be released to other parties safely. This process is usually called as privacy-preserving data publishing. In this monograph, we study how the data owner can modify the data and how the modified data can preserve privacy and protect sensitive information. Table of Contents: Introduction / Fundamental Concepts / One-Time Data Publishing / Multiple-Time Data Publishing / Graph Data / Other Data Types / Future Research Directions 140 pp. Englisch.