Data-Driven Cyber Prediction in Hybrid Warfare
Date
2019-06-17
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Abstract
Cyber Warfare, despite being a thoroughly discussed tactic, is consistently misunderstood and taken out of context. Cyberattacks, most often committed during hybrid warfare, are often studied apart from the physical attributes of war. There is a lack of literature that studies the interplay of cyber and physical attributes within hybrid warfare. By analyzing and assessing the Ukrainian Crisis, this thesis investigates how physical attributes may be used to predict cyberattacks based on real world data. Using the Axelrod-Iliev equation optimal timing of cyberattack against Ukraine could be determined and, from this, defensive postures could be suggested. To test if the Axelrod-Iliev equation held true, statistical analysis was used. The statistical analysis verified the findings of the Axelrod-Iliev equation and provided groundwork for future research in the subject area. The statistical analysis found a lack of correlation between Military Personnel/Policemen Killed/Wounded and cyberattacks, Civilians/Politicians Killed/Wounded and cyberattacks, Protests and cyberattacks. Conversely it strongly suggested links between Bombings and cyberattack, and Open Firing and cyberattacks, which can be expounded upon to further understand the interplay of cyber and physical attributes in hybrid warfare.
Keywords: Hybrid warfare, Cyber, Military, Ukraine, Russia, Data Analytics
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Keywords
Data Analytics, Ukraine, Russia, Cyber, Hybrid Warfare
Citation
Devereux, H. (2019). Data-Driven Cyber Prediction in Hybrid Warfare (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.