Title :
Logical vs. numerical inference on statistical databases
Author :
Chowdhury, Sumit Dutta ; Duncan, George T. ; Krishnan, Ramayya ; Roehrig, Stephen ; Mukherjee, Sumitra
Author_Institution :
John H. Heinz III Sch. of Public Policy & Manage., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
As computer databases have become more prevalent and comprehensive, they have prompted concerns about the confidentiality of sensitive information. Database administrators require effective policies to guard against disclosure of confidential information while at the same time providing reasonable access to legitimate users. A general method is available for determining if disclosure of sensitive information may result from inference over multiple database tables. This method relies on the logical structure of the tables, and is thus independent of the actual contents. After reviewing this method, we present new numerical techniques which in some cases allow inference of sensitive data even in instances pronounced safe by the logical method. These new techniques exploit the contents of the tables, and one makes use of a pair of new matrix operators. A real-world example of a multi-table inference process is given
Keywords :
data privacy; database theory; inference mechanisms; linear programming; matrix algebra; security of data; statistical databases; data confidentiality; legitimate users; linear programming; logical inference; logical structure; matrix operators; multiple database tables; multitable inference process; numerical inference; numerical techniques; policies; sensitive information; statistical databases; Authorization; Communication system control; Couplings; Cryptography; Data security; Databases; Linear programming; Medical services; Protection; Public policy;
Conference_Titel :
System Sciences, 1996., Proceedings of the Twenty-Ninth Hawaii International Conference on ,
Conference_Location :
Wailea, HI
Print_ISBN :
0-8186-7324-9
DOI :
10.1109/HICSS.1996.495374