The Scientific Workflow Integrity with Pegasus (SWIP) project improves the security and integrity of scientific data by integrating cryptographic integrity checking and provenance information into the Pegasus workflow management system (WMS). Complex workflows are commonplace in computational science and engineering applications and Pegasus is a popular WMS used in numerous scientific domains, e.g., astronomy, bioinformatics, earthquake science, gravitational wave physics, ocean science and neuroscience. For example, one project using Pegasus is LIGO (the Laser Interferometer Gravitational-Wave Observatory), which announced in early 2016 the first direct detection of gravitational waves.

The overarching goal of this project is to help enable more trustworthy science. One important facet of that is to ensure data has not been altered - either maliciously or accidentally. Digital signatures are one type of cryptographic support offered in SWIP that can help. By digitally signing data that is run through Pegasus, it is possible to assert the data has not changed. This helps ensure the integrity of the data and verify its provenance, providing greater trust in results. It is expected that solutions implemented for this project will be generic enough to apply to other workflow systems and applications, thereby helping a broad range of research with concerns about data integrity.

SWIP will be capable of operating across distributed cyberinfrastructure (CI), including dynamically-configurable CI. Pegasus has been integrated with the Open Resource Control Architecture (ORCA) to add assurances based on Pegasus’ dynamic provisioning capabilities for isolation and confidentiality.

The three-year project is funded by a $1 million grant from the National Science Foundation (NSF) as part of its Cybersecurity Innovation for Cyberinfrastructure (CICI) program. Von Welch (IU CACR) is the PI with Co-PIs Dr. Raquel Hill (IU SICE), Dr. Ilya Baldin (RENCI), and Dr. Ewa Deelman (USC/ISI). Dr. Steven Myers is a project alumni.

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The SWIP Project is supported by the National Science Foundation under Grant 1642070, 1642053, and 1642090. The views expressed do not necessarily reflect the views of the National Science Foundation or any other organization.