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Companies like Netflix increasingly use the cloud to deploy their business processes. Those processes often involve partnerships with other companies, and can be modeled as workflows. This shift towards the cloud environment has led to more and more data leaks and breaches, resulting in huge losses of money for businesses like the movie industry, as well as a loss of user privacy for businesses dealing with user data like the pharmaceutical industry.In this paper, we show how those workflows can be enforced while preventing data exposure. Following the principles of zerotrust, we develop an infrastructure using the isolation provided by a microservice architecture, to enforce owner policy. We show that our infrastructure is resilient to the set of attacks considered in our security model. We implement a simple, yet realistic, workflow with our infrastructure in a publicly available proof of concept. We then verify that the specified policy is correctly enforced by testing the deployment for policy violations, and estimate the overhead cost of authorization.

Companies like Netflix increasingly use the cloud to deploy their business processes. Those processes often involve partnerships with other companies, and can be modeled as workflows where the owner of the data at risk interacts with contractors to realize a sequence of tasks on the data to be secured.In practice, access control is an essential building block to deploy these secured workflows. This component is generally managed by administrators using high-level policies meant to represent the requirements and restrictions put on the workflow. Handling access control with a high-level scheme comes with the benefit of separating the problem of specification, i.e. defining the desired behavior of the system, from the problem of implementation, i.e. enforcing this desired behavior. However, translating such high-level policies into a deployed implementation can be error-prone.Even though semi-automatic and automatic tools have been proposed to assist this translation, policy verification remains highly challenging in practice. In this paper, our aim is to define and propose structures assisting the checking and correction of potential errors introduced on the ground due to a faulty translation or corrupted deployments. In particular, we investigate structures with formal foundations able to naturally model policies. Metagraphs, a generalized graph theoretic structure, fulfill those requirements: their usage enables to compare high-level policies to their implementation. In practice, we consider Rego, a language used by companies like Netflix and Plex for their release process, as a valuable representative of most common policy languages. We propose a suite of tools transforming and checking policies as metagraphs, and use them in a global framework to show how policy verification can be achieved with such structures. Finally, we evaluate the performance of our verification method.

Data leaks and breaches are on the rise. They result in huge losses of money for businesses like the movie industry, as well as a loss of user privacy for businesses dealing with user data like the pharmaceutical industry. Preventing data exposures is challenging, because the causes for such events are various, ranging from hacking to misconfigured databases. Alongside the surge in data exposures, the recent rise of microservices as a paradigm brings the need to not only secure traffic at the border of the network, but also internally, pressing the adoption of new security models such as zero-trust to secure business processes. Business processes can be modeled as workflows, where the owner of the data at risk interacts with contractors to realize a sequence of tasks on this data. In this paper, we show how those workflows can be enforced while preventing data exposure. Following the principles of zero-trust, we develop an infrastructure using the isolation provided by a microservice architecture, to enforce owner policy. We show that our infrastructure is resilient to the set of attacks considered in our security model. We implement a simple, yet realistic, workflow with our infrastructure in a publicly available proof of concept. We then verify that the specified policy is correctly enforced by testing the deployment for policy violations, and estimate the overhead cost of authorization.

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Companies such as Netflix increasingly use the cloud to deploy their business processes. Those processes often involve partnerships with other companies, and can be modeled as workflows where the owner of the data at risk interacts with contractors to realize a sequence of tasks on the data to be secured. In this paper, we first show how those workflows can be deployed and enforced while preventing data exposure. Second, this paper provides a global framework to enable the verification of workflow policies. Following the principles of zero-trust, we develop an infrastructure using the isolation provided by a microservice architecture to enforce owner policy. We implement a workflow with our infrastructure in a publicly available proof of concept. This work allows us to verify that the specified policy is correctly enforced by testing the deployment for policy violations, and find the overhead cost of authorization to be reasonable for the benefits. In addition, this paper presents a way to verify policies using a suite of tools transforming and checking policies as metagraphs. It is evident from the results that our verification method is very efficient regarding the size of the policies. Overall, this infrastructure and the mechanisms that verify the policy is correctly enforced, and then correctly implemented, help us deploy workflows in the cloud securely.