Diophantine Inference on a Statistical Database

Rowe, Neil C.

dc.contributor.author	Rowe, Neil C.
dc.date.accessioned	2013-09-18T16:54:57Z
dc.date.available	2013-09-18T16:54:57Z
dc.date.issued	2008
dc.identifier.citation	Information Processing Letters, 18 (1984), 25-31.
dc.identifier.uri	https://hdl.handle.net/10945/36437
dc.description	This paper appeared in Information Processing Letters, 18 (1984), 25-31. The equations were redrawn in 2008 and some corrections made.	en_US
dc.description.abstract	A statistical database is said to be compromisable if individual data items can be inferred from queryable values of statistical aggregates (mean, maximum, count, etc.) ((Denning82), ch. 6). We discuss here some methods, which while only leading to compromise of individual records on occasion, do lead to powerful inferences of other statistical characteristics of a database which may also be sensitive information. These methods use a new technique that has not apparently heretofore been explored, solution of simultaneous Diophantine (integer-solution) equations.	en_US
dc.description.sponsorship	This work is part of the Knowledge Base Management Systems Project at Stanford University, under contract #N00039-82-G-0250 from the Defense Advanced Research Projects Agency of the United States Department of Defense	en_US
dc.publisher	Monterey, California. Naval Postgraduate School	en_US
dc.title	Diophantine Inference on a Statistical Database	en_US
dc.type	Conference Paper	en_US
dc.contributor.department	Computer Science (CS)
dc.description.distributionstatement	Approved for public release; distribution is unlimited.