Quantification of Integrity
| dc.contributor.author | Clarkson, Michael R. | |
| dc.contributor.author | Schneider, Fred B. | |
| dc.date.accessioned | 2011-01-12T19:36:34Z | |
| dc.date.available | 2011-01-12T19:36:34Z | |
| dc.date.issued | 2011-01-12 | |
| dc.description.abstract | Three integrity measures are introduced: contamination, channel suppression, and program suppression. Contamination is a measure of how much untrusted information reaches trusted outputs; it is the dual of leakage, which is a measure of information-flow confidentiality. Channel suppression is a measure of how much information about inputs to a noisy channel is missing from channel outputs. And program suppression is a measure of how much information about the correct output of a program is lost because of attacker influence and implementation errors. Program and channel suppression do not have confidentiality duals. As a case study, the relationship between quantitative integrity, confidentiality, and database privacy is examined. | en_US |
| dc.description.sponsorship | Supported in part by ONR grant N00014-09-1-0652, AFOSR grant F9550-06-0019, NSF grants 0430161, 0964409, and CCF-0424422 (TRUST), and a gift from Microsoft Corporation. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1813/22012 | |
| dc.language.iso | en_US | en_US |
| dc.relation.hasversion | Revises and expands an earlier tech report: http://ecommons.library.cornell.edu/handle/1813/14470 | en_US |
| dc.subject | integrity | en_US |
| dc.subject | quantitative information flow | en_US |
| dc.subject | information theory | en_US |
| dc.subject | database privacy | en_US |
| dc.title | Quantification of Integrity | en_US |
| dc.type | article | en_US |
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- revised January 2012