Diophantine Inference on a Statistical Database
| dc.contributor.author | Rowe, Neil C. | |
| dc.contributor.department | Computer Science (CS) | |
| dc.date.accessioned | 2013-09-18T16:54:57Z | |
| dc.date.available | 2013-09-18T16:54:57Z | |
| dc.date.issued | 2008 | |
| 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.distributionstatement | Approved for public release; distribution is unlimited. | |
| 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.identifier.citation | Information Processing Letters, 18 (1984), 25-31. | |
| dc.identifier.uri | https://hdl.handle.net/10945/36437 | |
| 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 |
| dspace.entity.type | Publication |
