A Dynamical Systems Approach for Detecting Cyberattacks in Software-Defined Networks

We propose a novel foundation for a mathematical framework to model and understand the dynamic behavior of Software-Defined Networks (SDNs), enabling the development of new algorithms for reliable cyberattack detection. SDNs, increasingly adopted in critical military networks, present unique challenges to traditional statistical-based detection methods due to their rapidly changing components and configurations. The December 2015 cyberattack on the Ukrainian power grid, where attackers exploited the flexibility of SDNs to disrupt operations, underscores the urgency of developing robust detection mechanisms. Our approach combines dynamical systems theory with persistent homology, a tool from topological data analysis, to overcome the limitations of current methods and address the dynamic nature of SDNs. This innovative approach promises to revolutionize cyberattack detection in SDN environments, offering enhanced protection for critical infrastructure.