Modeling Data Integrity Threats for Scientific Workflows Using OSCRP and MITRE ATT&CK

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.