Modeling Data Integrity Threats for Scientific Workflows Using OSCRP and MITRE ATT&CK
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Abstract
Guaranteeing the data integrity of scientific workflows
and their associated data products, in the face of nonmalicious
and malicious threats, is of paramount importance for
the validity and credibility of scientific research. In this work,
we describe how we can leverage two popular cybersecurity
classification frameworks - OSCRP and MITRE ATT&CK®,
to systematically model threats to the integrity of scientific
workflows and data in a research setting. We enumerate nonmalicious
and malicious threats to the integrity of scientific
workflows, and present the relevant assets, concerns, avenues of
attacks and impact of the threats in typical scientific workflow
execution scenarios.
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Data Integrity, threat model, non-malicious, scientific workflows, OSCRP, MITRE ATT&CK
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This work may be protected by copyright unless otherwise stated.
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Working Paper