Foreword by Pierangela Samarati
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; it allows the data owner to
outsource not only the data but the security policy itself. The
last section of this book investigates the problem of executing
queries over possible data distributed at different servers. Case
Studies will be provided.
About this book:
Exclusively focuses on addressing protection of confidential
information in the emerging data outsourcing scenarios.
Presents relevant and critical novel problems and novel
techniques, a precious reference point to students, researchers,
and developers in this field.
Provides a comprehensive overview of the data protection problem
in outsourcing scenarios, as well as a rigorous analysis and
formalization of the problem and solutions to it.
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.
General
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