Quantifying leakage in the presence of unreliable sources of information
Quantifying leakage in the presence of unreliable sources of information
Belief and min-entropy leakage are two well-known approaches to quantify information flow in security systems. Both concepts stand as alternatives to the traditional approaches founded on Shannon entropy and mutual information, which were shown to provide inadequate security guarantees. In this paper we unify the two concepts in one model so as to cope with the frequent (potentially inaccurate, misleading or outdated) attackers’ side information about individuals on social networks, online forums, blogs and other forms of online communication and information sharing. To this end we propose a new metric based on min-entropy that takes into account the adversary’s beliefs.
27-52
Hamadou, Sardouna
a3681473-229f-423a-8113-b466cd1b5e98
Palamidessi, Catuscia
a62c01bb-aec0-490b-bd05-b9081954b88f
Sassone, Vladimiro
df7d3c83-2aa0-4571-be94-9473b07b03e7
September 2017
Hamadou, Sardouna
a3681473-229f-423a-8113-b466cd1b5e98
Palamidessi, Catuscia
a62c01bb-aec0-490b-bd05-b9081954b88f
Sassone, Vladimiro
df7d3c83-2aa0-4571-be94-9473b07b03e7
Hamadou, Sardouna, Palamidessi, Catuscia and Sassone, Vladimiro
(2017)
Quantifying leakage in the presence of unreliable sources of information.
Journal of Computer and System Sciences, 88, .
(doi:10.1016/j.jcss.2017.03.013).
Abstract
Belief and min-entropy leakage are two well-known approaches to quantify information flow in security systems. Both concepts stand as alternatives to the traditional approaches founded on Shannon entropy and mutual information, which were shown to provide inadequate security guarantees. In this paper we unify the two concepts in one model so as to cope with the frequent (potentially inaccurate, misleading or outdated) attackers’ side information about individuals on social networks, online forums, blogs and other forms of online communication and information sharing. To this end we propose a new metric based on min-entropy that takes into account the adversary’s beliefs.
Text
belief.pdf
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More information
Accepted/In Press date: 19 August 2016
e-pub ahead of print date: 3 April 2017
Published date: September 2017
Organisations:
Electronics & Computer Science
Identifiers
Local EPrints ID: 403793
URI: http://eprints.soton.ac.uk/id/eprint/403793
ISSN: 0022-0000
PURE UUID: ef73df97-a547-4add-8b8c-835b2538ebad
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Date deposited: 11 Dec 2016 17:18
Last modified: 10 Sep 2024 01:40
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Contributors
Author:
Sardouna Hamadou
Author:
Catuscia Palamidessi
Author:
Vladimiro Sassone
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