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F. Chin and G. Ozsoyoglu. Auditing and infrence control in statistical databases. IEEE Transactions on Software Eng., SE-8(6):113--139, April 1982.

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Information Sharing Across Private Databases - Agrawal, Evfimievski, Srikant (2003)   (16 citations)  (Correct)

....restriction techniques from the statistical database literature [1, 44] can also help. These techniques include restricting the size of query results [17, 23] controlling the overlap among successive queries [19] and keeping audit trails of all answered queries to detect possible compromises [13]. Schema Discovery and Heterogeneity We do not address the question of how to find which database contains which tables and what the attribute names are; we assume that the database schemas are known. We also do not address issues of schema heterogeneity. See [21, 29] and references therein for ....

F. Chin and G. Ozsoyoglu. Auditing and infrence control in statistical databases. IEEE Transactions on Software Eng., SE-8(6):113--139, April 1982.


Hippocratic Databases - Agrawal, Kiernan, Srikant, Xu (2002)   (12 citations)  (Correct)

....classified into query restriction and data perturbation. The query restriction family includes restricting the size of query results [13] 18] controlling the overlap among successive queries [14] keeping audit trails of all answered queries and constantly checking for possible compromises [8], suppression of data cells of small size [9] and clustering entities into mutually exclusive atomic populations [61] The perturbation family includes swapping values between records [12] replacing the original database by a sample from the same distribution [33] 42] adding noise to the ....

F. Chin and G. Ozsoyoglu. Auditing and infrence control in statistical databases. IEEE Trans. on Software Eng., SE-8(6):113--139, April 1982.


Privacy-Preserving Data Mining - Agrawal, Srikant (2000)   (98 citations)  (Correct)

....and data perturbation. The query restriction family includes restricting the size of query result (e.g. Fel72] DDS79] controlling the overlap amongst successive queries (e.g. DJL79] keeping audit trail of all answered queries and constantly checking for possible compromise (e.g. CO82] suppression of data cells of small size (e.g. Cox80] and clustering entities into mutually exclusive atomic populations (e.g. YC77] The perturbation family includes swapping values between records (e.g. Den82] replacing the original database by a sample from the same distribution ....

F.Y. Chin and G. Ozsoyoglu. Auditing and infrence control in statistical databases. IEEE Trans. Softw. Eng., SE-8(6):113--139, April 1982.


Information Sharing across Private Databases - Agrawal, Evfimievski, Srikant (2003)   (16 citations)  (Correct)

No context found.

F. Chin and G. Ozsoyoglu. Auditing and infrence control in statistical databases. IEEE Transactions on Software Eng., SE-8(6):113--139, April 1982.

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