Neorealist Analysis of Security Dilemma in Cyberspace; A Quantitative Study

Two crucial factors have urged IR academia to account for state behavior in cyberspace: the increasing volume of cyber attacks and the rising scale of damage induced by these attacks. This has led to a series of initiatives appealing to the grand theories of IR in order to scrutinize state behavior in depth. Following a similar pattern, this work intends to contribute to IR academia by presenting a neorealist analysis of state behavior in cyberspace by relying on quantitative methods. Two regression analyses, one using a linear and the other using a negative binomial algorithm, were conducted using a dataset consisting of 4,099 samples. The analyses indicate that as states build more cyber security capacity, they tend to execute more disruptive actions against other states in cyberspace. Both regression models were subsequently trained using artificial neural networks (ANNs) and showed improvements in their metrics compared to their traditional regression counterparts.