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International audience ; —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.

International audience ; —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 ...

A model of cloud services is emerging whereby a few trusted providers manage the underlying hardware and communications whereas many companies build on this infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS applications. From the start, strong isolation between cloud tenants was seen to be of paramount importance, provided first by virtual machines (VM) and later by containers, which share the operating system (OS) kernel. Increasingly it is the case that applications also require facilities to effect isolation and protection of data managed by those applications. They also require flexible data sharing with other applications, often across the traditional cloud-isolation boundaries; for example, when government, consisting of different departments, provides services to its citizens through a common platform. These concerns relate to the management of data. Traditional access control is application and principal/role specific, applied at policy enforcement points, after which there is no subsequent control over where data flows;a crucial issue once data has left its owner's control by cloud-hosted applications andwithin cloud-services. Information Flow Control (IFC), in addition, offers system-wide, end-To-end, flow control based on the properties of the data. We discuss the potential of cloud-deployed IFC for enforcing owners' data flow policy with regard to protection and sharing, aswell as safeguarding against malicious or buggy software. In addition, the audit log associated with IFC provides transparency and offers system-wide visibility over data flows. This helps those responsible to meet their data management obligations, providing evidence of compliance, and aids in the identification ofpolicy errors and misconfigurations. We present our IFC model and describe and evaluate our IFC architecture and implementation (CamFlow). This comprises an OS level implementation of IFC with support for application management, together with an IFC-enabled middleware.