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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.
