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Quantification of integrity†

Published online by Cambridge University Press:  10 November 2014

MICHAEL R. CLARKSON  and
FRED B. SCHNEIDER
MICHAEL R. CLARKSON
Affiliation:
Department of Computer Science, Cornell University, Ithaca, NY, 14853, USA Email: clarkson@cs.cornell.edu
FRED B. SCHNEIDER
Affiliation:
Department of Computer Science, Cornell University, Ithaca, NY, 14853, USA Email: fbs@cs.cornell.edu
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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 the 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 interesting confidentiality duals. As a case study, a quantitative relationship between integrity, confidentiality and database privacy is examined.

Information

Type
Special Issue: Quantitative Information Flow
Information
Mathematical Structures in Computer Science , Volume 25 , Issue 2: Quantitative Information Flow , February 2015 , pp. 207 - 258
Copyright
Copyright © Cambridge University Press 2014 

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Footnotes

†

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.

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