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Abstract
Designing programs that do not leak confidential information continues to be a challenge. Part of the difficulty arises when partial information leaks are inevitable, implying that design interventions can only limit rather than eliminate their impact.
We show, by example, how to gain a better understanding of the consequences of information leaks by modelling what adversaries might be able to do with any leaked information.
Our presentation is based on the theory of Quantitative Information Flow, but takes an experimental approach to explore potential vulnerabilities in program designs. We make use of the tool Kuifje [12] to interpret a small programming language in a probabilistic semantics that supports quantitative information flow analysis.
We show, by example, how to gain a better understanding of the consequences of information leaks by modelling what adversaries might be able to do with any leaked information.
Our presentation is based on the theory of Quantitative Information Flow, but takes an experimental approach to explore potential vulnerabilities in program designs. We make use of the tool Kuifje [12] to interpret a small programming language in a probabilistic semantics that supports quantitative information flow analysis.
Original language | English |
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Title of host publication | Mathematics of program construction |
Subtitle of host publication | 13th International Conference, MPC 2019, Proceedings |
Editors | Graham Hutton |
Place of Publication | Cham |
Publisher | Springer, Springer Nature |
Pages | 1-17 |
Number of pages | 17 |
ISBN (Electronic) | 9783030336363 |
ISBN (Print) | 9783030336356 |
DOIs | |
Publication status | Published - 2019 |
Event | 13th International Conference on the Mathematics of Program Construction, MPC 2019 - Porto, Portugal Duration: 7 Oct 2019 → 9 Oct 2019 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11825 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 13th International Conference on the Mathematics of Program Construction, MPC 2019 |
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Country/Territory | Portugal |
City | Porto |
Period | 7/10/19 → 9/10/19 |
Keywords
- Quantitative Information Flow
- Probabilistic program semantics
- Security
- Confidentiality
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- 1 Finished
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More information for better utility; less information for better privacy
McIver, A., Morgan, C., Teague, V., Schneider, S., MQRES, M. & PhD Contribution (ARC), P. C.
26/03/14 → 31/12/20
Project: Research