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

dc.contributor.authorAbhinit, Ishan
dc.contributor.authorAdams, Emily K
dc.contributor.authorChase, Brian
dc.contributor.authorMandal, Anirban
dc.contributor.authorXin, Yufeng
dc.contributor.authorVahi, Karan
dc.contributor.authorRynge, Mats
dc.contributor.authorDeelman, Ewa
dc.date.accessioned2022-09-13T17:19:22Z
dc.date.available2022-09-13T17:19:22Z
dc.date.issued2022-08-22
dc.description.abstractGuaranteeing 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.en
dc.description.sponsorshipNSF Award #1839900en
dc.identifier.urihttps://hdl.handle.net/2022/28188
dc.language.isoenen
dc.subjectData Integrity, threat model, non-malicious, scientific workflows, OSCRP, MITRE ATT&CKen
dc.titleModeling Data Integrity Threats for Scientific Workflows Using OSCRP and MITRE ATT&CKen
dc.typeWorking Paperen

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