Abstract
Concern about data leakage is holding back more widespread adoption of cloud computing by companies and public institutions alike. To address this, cloud tenants/applications are traditionally isolated in virtual machines or containers. But an emerging requirement is for cross-application sharing of data, for example, when cloud services form part of an IoT architecture. Information Flow Control (IFC) is ideally suited to achieving both isolation and data sharing as required. IFC enhances traditional Access Control by providing continuous, data-centric, cross-application, end-to-end control of data flows. However, large-scale data processing is a major requirement of cloud computing and is infeasible under standard IFC. We present a novel, enhanced IFC model that subsumes standard models. Our IFC model supports 'Big Data' processing, while retaining the simplicity of standard IFC and enabling more concise, accurate and maintainable expression of policy.
Original language | English |
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Title of host publication | Proceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 524-531 |
Number of pages | 8 |
ISBN (Electronic) | 9781467372879 |
DOIs | |
Publication status | Published - 19 Aug 2015 |
Event | 8th IEEE International Conference on Cloud Computing, CLOUD 2015 - New York, United States Duration: 27 Jun 2015 → 2 Jul 2015 |
Conference
Conference | 8th IEEE International Conference on Cloud Computing, CLOUD 2015 |
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Country/Territory | United States |
City | New York |
Period | 27/06/15 → 2/07/15 |
Keywords
- Data Management
- Information Flow Control
- Security