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  1. Proceedings of the third ACM SIGPLAN workshop on Programming languages and analysis for security (PLAS '08)
  2. Lagrange multipliers and maximum information leakage in different observational models
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Simulating midlet's security claims with automata modulo theory
A compiler-based infrastructure for software-protection
Resource bound analysis for database queries
Information flow security of multi-threaded distributed programs
Aspect-oriented in-lined reference monitors
A security domain model to assess software for exploitable covert channels
Evaluating the cost reduction of static code analysis for software security
Securing nonintrusive web encryption through information flow
Verified enforcement of stateful information release policies
Static path conditions for Java
A type system for data-flow integrity on windows vista
Lagrange multipliers and maximum information leakage in different observational models
Dominator-tree analysis for distributed authorization

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Lagrange multipliers and maximum information leakage in different observational models

Content Provider ACM Digital Library
Author Malacaria, Pasquale Chen, Han
Abstract This paper explores two fundamental issues in Language based security. The first is to provide a quantitative definition of information leakage valid in several attacker's models. We consider attackers with different capabilities; the strongest one is able to observe the value of the low variables at each step during the execution of a program; the weakest one can only observe a single low value at some stage of the execution. We will provide a uniform definition of leakage, based on Information Theory, that will allow us to formalize and prove some intuitive relationships between the amount leaked by the same program in different models. The second issue is Channel Capacity, which in security terms amounts to answering the questions: given a program and an observational model, what is the maximum amount that the program can leak? And which input distribution causes the maximum leakage? To answer those questions we will introduce techniques from constrained non-linear optimization, mainly Lagrange multipliers and we will show how they provide a workable solution in all observational models considered. In the simplest setting, i.e. under minimal constraints, we will show that channel capacity is achieved by any input distribution which induces a uniform distribution on the observables.
Starting Page 135
Ending Page 146
Page Count 12
File Format PDF
ISBN 9781595939364
DOI 10.1145/1375696.1375713
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2008-06-07
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Lagrange multipliers Security Information theory
Content Type Text
Resource Type Article
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