Strategic Defense against Hybrid Threats under Emerging Disruptive Technologies: A Stochastic Modeling Framework

Abstract

The fundamental unpredictability of Emerging Disruptive Technologies creates profound strategic asymmetries in hybrid threats, as defenders must prepare for unknown capabilities while attackers exploit breakthroughs. This research introduces a new model to analyze how technological uncertainty transforms optimal strategies for defensive actors, proving essential for developing robust strategies as the pace of technological innovation accelerates and the window between innovation and weaponization narrows. In this work, technological uncertainty is modelled as a stochastic evolutionary process, focusing on the defender's challenge of resource allocation. Through a parametrized model design, the framework provides high customisability for different scenarios and technology-specific insights relevant for developing optimized allocations of defense resources. We compare a naive baseline resource allocation against an optimized allocation in a simulated scenario, showcasing the need for differentiated defense postures and showcasing the need for differentiated defense postures and illustrating a novel pathway for reasoning under deep technological uncertainty. The experiments show a significant superiority of technology-tailored resource allocations, reducing overall attack impact and planning uncertainty.

Keywords: Emerging Disruptive Technologies (EDTs), Hybrid Threats, Stochastic Process, Modeling

DOI: 10.54941/ahfe1007080