Download Preserving Privacy in Data Outsourcing by Sara Foresti (auth.) PDF

By Sara Foresti (auth.)

Privacy necessities have an expanding effect at the recognition of contemporary purposes. advertisement and felony laws call for that privateness promises be supplied every time delicate info is saved, processed, or communicated to exterior events. present techniques encrypt delicate info, therefore lowering question execution potency and fighting selective details free up.

Preserving privateness in info Outsourcing provides a accomplished technique for safeguarding hugely delicate details while it really is saved on structures that aren't below the information owner's regulate. The strategy illustrated combines entry keep watch over and encryption, imposing entry keep an eye on through dependent encryption. This resolution, coupled with effective algorithms for key derivation and distribution, offers effective and safe authorization administration on outsourced information, permitting the information proprietor to outsource not just the information however the defense coverage itself. to lessen the quantity of knowledge to be encrypted the e-book additionally investigates information fragmentation as a potential technique to shield privateness of information institutions and supply fragmentation as a complementary capability for safeguarding privateness: institutions damaged via fragmentation could be obvious merely to clients licensed (by figuring out the correct key) to hitch fragments. The ebook eventually investigates the matter of executing queries over attainable information dispensed at assorted servers and which needs to be managed to make sure delicate details and delicate institutions be noticeable in simple terms to events approved for that. Case reports are supplied through the book.

Privacy, info mining, facts security, information outsourcing, digital trade, desktop studying pros and others operating in those comparable fields will locate this booklet a worthwhile asset, in addition to basic institutions resembling ACM, IEEE and administration technological know-how. This booklet can also be compatible for complex point scholars and researchers focusing on machine technology as a secondary textual content or reference book.

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Extra resources for Preserving Privacy in Data Outsourcing

Sample text

Each plaintext value vh is associated with a scaling factor sh . When vh is split into n index values, namely i1 , . . , in , each index entry in the B-tree corresponding to ih is replicated sh times. Note that all sh replicas of the index point to the same block of tuples in the encrypted database. After scaling has been applied, the index frequency distribution is not uniform any more. Without knowing the scaling factor used, it is not possible for the attacker to reconstruct the correspondence between plaintext and index values.

Sovereign joins [3] represent an interesting alternative solution for secure information sharing. This method is based on a secure coprocessor, which is involved in query execution, and exploits cryptography to grant privacy. The advantage of sovereign joins is that they extend the plans that allow an execution in the scenario we present; the main obstacle is represented by their high computational cost, due to the use of specific asymmetric cryptography primitives, that make them currently not applicable when large collections of sensitive information must be combined.

B-tree data structure is similar to B+ tree data structure, but internal vertices directly refer to tuples in the database and leaves of the tree are not linked in a unique list. An OPESS index can be usefully adopted for each attribute ai j in the relation schema Ri , provided ai j is defined over a partially ordered domain. The index is built by the data owner over the plaintext values of the attribute, and then stored on the remote server, together with the encrypted database. Differently from B+ tree indexing structure, the B-tree data structure exploited by OPESS is built on index values, and not on plaintext values.

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