The rapid expansion of drone delivery services, with over 2,000 commercial deliveries made daily worldwide, has contributed to a booming market valued at USD 32.5 billion in 2023. Projections suggest it will exceed USD 78.5 billion by 2032. This growth is driven by advancements in drone technology, reduced costs, rising consumer demand for faster delivery, and improved regulatory frameworks.
However, as drones increasingly operate in swarms, cybersecurity concerns are growing. These swarms rely on extensive data sharing for task scheduling, creating vulnerabilities. An attack on one drone in the swarm can trigger a chain reaction across the entire network, similar to the risks faced by hotel chains or supply chains.
A recent study by researchers from the School of Mathematical and Statistical Sciences at Arizona State University addresses these concerns with a dynamic percolation model. Using probabilistic graph theory and spatial Poisson point processes, the model examines how cybersecurity risks spread across drone delivery networks. The study analyzes both single-layer and multi-layer models to assess potential losses in drone swarms and turret networks during cyberattacks, factoring in system parameters like signal strength, communication range, and node vulnerability.
Simulation results reveal that optimizing defense resources and improving communication protocols can significantly reduce losses when percolation risks are low. Conversely, high percolation probability increases losses.
The findings, published in Risk Sciences, provide valuable insights for cybersecurity risk assessments in drone delivery services and offer practical guidance for policymakers, risk managers, and cybersecurity professionals in developing effective defense strategies.
