Exploring Bivariate Correlations in Cyber Risk on an Industrial Level: Empirical Evidence From Greece and the European Economic Area

In the rapidly evolving domain of cybercrime, understanding the intricate dynamics between industry-specific characteristics and cyber risk ramifications is critical for developing robust risk management strategies. This study delves into the bivariate relationships between annual cyber-attack rates and various industry attributes. Utilizing time-series data as well as both Pearson and Kendall correlation analyses, we assess the linear and ordinal associations across a comprehensive dataset encompassing multiple industries. Our findings reveal that the telecommunications and digital infrastructure industries display a significant inverse relationship between cyber incident rates and systemic risk, an unexpected observation indicating that improved awareness or control of systemic risk may lead to reduced incident rates. On the other hand, the banking sector's direct correlation suggests that as systemic risk rises, so do incident rates, likely because of the sector's attractive high-value data targets. The outcomes of this bivariate exploration complement our previous empirical analysis presented in the article The Financial Impact of Cyber Risk: Empirical Evidence from Greece and the European Economic Area, conducted by the same author, offering a granular view of the cyber risk landscape. This paper aims to inform stakeholders on the pivotal interactions between industrial dynamics and cybersecurity outcomes, fostering informed strategies to mitigate risk and safeguard economic interests.