Managing Big Data with Information Flow Control

Thomas F.J.M. Pasquier, Jatinder Singh, Jean Bacon, Olivier Hermant

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)


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 languageEnglish
Title of host publicationProceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)9781467372879
Publication statusPublished - 19 Aug 2015
Event8th IEEE International Conference on Cloud Computing, CLOUD 2015 - New York, United States
Duration: 27 Jun 20152 Jul 2015


Conference8th IEEE International Conference on Cloud Computing, CLOUD 2015
Country/TerritoryUnited States
CityNew York


  • Data Management
  • Information Flow Control
  • Security


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