Managing Big Data with Information Flow Control

Thomas Pasquier (1) , Jatinder Singh (1) , Jean Bacon (1) , Olivier Hermant (2, 3)

1 CAM - University of Cambridge [UK]
2 Mines Paris - PSL (École nationale supérieure des mines de Paris)
3 CRI - Centre de Recherche en Informatique

—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. I. INTRODUCTION Concern about data leakage is holding back more widespread adoption of cloud computing by companies and public institutions. There is an increasing volume of applicable legislation and regulation [1], but ensuring and demonstrating compliance by cloud service providers and third parties is problematic. In recent work we have explored the use of Information Flow Control (IFC) for cloud and distributed computing , based on a proof-of-concept implementation (FlowK) of the standard IFC model as a basis for evaluation [2]. Based on this experience, we believe that the deployment of IFC to augment traditional authentication and authorisation has the potential to make a substantial contribution to the security of distributed and cloud systems, both through enforcement mechanisms and demonstration of compliance through audit. However, the use of IFC for large-scale data sharing and analytics is problematic using the standard IFC model. In this paper we present an enhanced IFC model which, while retaining the simplicity of expression and implementation of the standard model, easily extends to large scale. Much work remains to be done, particularly when cloud services are incorporated as part of wide-scale distributed systems, as in the Internet of Things (IoT). In a cloud context , tenants/applications are traditionally isolated in virtual machines or containers. An emerging requirement is for cross-application sharing of data, particularly when cloud services are used for IoT. IFC is ideally suited to achieving both isolation and data sharing as required [3]. If IFC is incorporated into cloud service provision as part of PaaS or SaaS clouds, it can provide continuous, data-centric access control policy within and across applications, see §II.

Mots clés: Information Flow Control; Data Management; Security

Domaines: Performance et fiabilité [cs.PF]; Cryptographie et sécurité [cs.CR]; Informatique [cs]

Thomas Pasquier, Jatinder Singh, Jean Bacon, Olivier Hermant. Managing Big Data with Information Flow Control. 8th IEEE International Conference on Cloud Computing (CLOUD 2015), Jun 2015, New York, United States. ⟨hal-01260014⟩