Delegation Protocols in Human-Centric Workflows

International audienceOrganisations are facilitated and conducted using workflow management systems. Currently, we observe a tendency moving away from strict workflow modelling towards dynamic approaches supporting human interactions when deploying a workflow. One specific approach ensuring human-centric workflows is task delegation. Delegating a task may require an access to specific and potentially sensitive data that have to be secured and specified into authorisation policies. In this paper, we propose a modelling approach to secure delegation. In doing so, we define delegation protocols supporting specific constraints based on both workflow and access control systems. Moreover, we develop an advanced access control framework to integrate delegation constraints within existing policies. The novelty consists in the proactivity aspect of our framework to cope with dynamic delegation of authority in authorisation policies

A Secure Task Delegation Model for Workflows

International audienceWorkflow management systems provide some of the required technical means to preserve integrity, confidentiality and availability at the control-, data- and task assignment layers of a workflow. We currently observe a move away from predefined strict workflow enforcement approaches towards supporting exceptions which are difficult to foresee when modelling a workflow. One specific approach for exception handling is that of task delegation. The delegation of a task from one principal to another, however, has to be managed and executed in a secure way, in this context implying the presence of a fixed set of delegation events. In this paper, we propose first and foremost, a secure task delegation model within a workflow. The novel part of this model is separating the various aspects of delegation with regards tousers, tasks, events and data, portraying them in terms of a multi-layered state machine. We then define delegation scenarios and analyse additional requirements to support secure task delegation over these layers. Moreover, we detail a delegation protocol with a specific focus on the initial negotiation steps between the involved principals

SciTokens: Capability-Based Secure Access to Remote Scientific Data

The management of security credentials (e.g., passwords, secret keys) for computational science workflows is a burden for scientists and information security officers. Problems with credentials (e.g., expiration, privilege mismatch) cause workflows to fail to fetch needed input data or store valuable scientific results, distracting scientists from their research by requiring them to diagnose the problems, re-run their computations, and wait longer for their results. In this paper, we introduce SciTokens, open source software to help scientists manage their security credentials more reliably and securely. We describe the SciTokens system architecture, design, and implementation addressing use cases from the Laser Interferometer Gravitational-Wave Observatory (LIGO) Scientific Collaboration and the Large Synoptic Survey Telescope (LSST) projects. We also present our integration with widely-used software that supports distributed scientific computing, including HTCondor, CVMFS, and XrootD. SciTokens uses IETF-standard OAuth tokens for capability-based secure access to remote scientific data. The access tokens convey the specific authorizations needed by the workflows, rather than general-purpose authentication impersonation credentials, to address the risks of scientific workflows running on distributed infrastructure including NSF resources (e.g., LIGO Data Grid, Open Science Grid, XSEDE) and public clouds (e.g., Amazon Web Services, Google Cloud, Microsoft Azure). By improving the interoperability and security of scientific workflows, SciTokens 1) enables use of distributed computing for scientific domains that require greater data protection and 2) enables use of more widely distributed computing resources by reducing the risk of credential abuse on remote systems.Comment: 8 pages, 6 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US