DocumentCode :
1709289
Title :
Managing Big Data with Information Flow Control
Author :
Pasquier, Thomas F. J. M. ; Singh, Jatinder ; Bacon, Jean ; Hermant, Olivier
Author_Institution :
Comput. Lab., Univ. of Cambridge, Cambridge, UK
fYear :
2015
Firstpage :
524
Lastpage :
531
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.
Keywords :
Big Data; Internet of Things; authorisation; cloud computing; Big Data management; IFC; IoT architecture; access control; cloud computing; cloud services; cloud tenants; containers; cross-application data sharing; data flows; data leakage; information flow control; large-scale data processing; virtual machines; Access control; Companies; Context; Data models; Hospitals; Standards; Data Management; Information Flow Control; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4673-7286-2
Type :
conf
DOI :
10.1109/CLOUD.2015.76
Filename :
7214086
Link To Document :
بازگشت