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Preserving Privacy in Data Outsourcing [electronic resource] / by Sara Foresti.

By: Contributor(s): Material type: TextTextSeries: Advances in Information Security ; 51Publisher: Boston, MA : Springer US, 2011Description: XV, 180 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781441976598
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 005.8 23
LOC classification:
  • QA76.9.A25
Online resources:
Contents:
Introduction -- Related work -- Selective encryption to enforce access control -- Combining fragmentation and encryption to protect data privacy -- Distributed query processing under safely composed permissions -- Conclusions.
In: Springer eBooksSummary: Privacy requirements have an increasing impact on the realization of modern applications. Commercial and legal regulations demand that privacy guarantees be provided whenever sensitive information is stored, processed, or communicated to external parties. Current approaches encrypt sensitive data, thus reducing query execution efficiency and preventing selective information release. Preserving Privacy in Data Outsourcing presents a comprehensive approach for protecting highly sensitive information when it is stored on systems that are not under the data owner's control. The approach illustrated combines access control and encryption, enforcing access control via structured encryption. This solution, coupled with efficient algorithms for key derivation and distribution, provides efficient and secure authorization management on outsourced data, allowing the data owner to outsource not only the data but the security policy itself. To reduce the amount of data to be encrypted the book also investigates data fragmentation as a possible way to protect privacy of data associations and provide fragmentation as a complementary means for protecting privacy: associations broken by fragmentation will be visible only to users authorized (by knowing the proper key) to join fragments. The book finally investigates the problem of executing queries over possible data distributed at different servers and which must be controlled to ensure sensitive information and sensitive associations be visible only to parties authorized for that. Case Studies are provided throughout the book. Privacy, data mining, data protection, data outsourcing, electronic commerce, machine learning professionals and others working in these related fields will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science. This book is also suitable for advanced level students and researchers concentrating on computer science as a secondary text or reference book.
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Item type Current library Call number Status Date due Barcode
E-Book E-Book Central Library Available E-39050

Introduction -- Related work -- Selective encryption to enforce access control -- Combining fragmentation and encryption to protect data privacy -- Distributed query processing under safely composed permissions -- Conclusions.

Privacy requirements have an increasing impact on the realization of modern applications. Commercial and legal regulations demand that privacy guarantees be provided whenever sensitive information is stored, processed, or communicated to external parties. Current approaches encrypt sensitive data, thus reducing query execution efficiency and preventing selective information release. Preserving Privacy in Data Outsourcing presents a comprehensive approach for protecting highly sensitive information when it is stored on systems that are not under the data owner's control. The approach illustrated combines access control and encryption, enforcing access control via structured encryption. This solution, coupled with efficient algorithms for key derivation and distribution, provides efficient and secure authorization management on outsourced data, allowing the data owner to outsource not only the data but the security policy itself. To reduce the amount of data to be encrypted the book also investigates data fragmentation as a possible way to protect privacy of data associations and provide fragmentation as a complementary means for protecting privacy: associations broken by fragmentation will be visible only to users authorized (by knowing the proper key) to join fragments. The book finally investigates the problem of executing queries over possible data distributed at different servers and which must be controlled to ensure sensitive information and sensitive associations be visible only to parties authorized for that. Case Studies are provided throughout the book. Privacy, data mining, data protection, data outsourcing, electronic commerce, machine learning professionals and others working in these related fields will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science. This book is also suitable for advanced level students and researchers concentrating on computer science as a secondary text or reference book.

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