With the rapid development of drone delivery services, there are now more than 2,000 commercial drone delivery every day worldwide. The global market size reached USD 32.5 billion in 2023 and is expected to exceed USD 78.5 billion by 2032. Advance in drone technology, declining cost, increasing demand for consumer for efficient distribution, and reform of regulatory structure contributed to this development trend.
Since drones work collaborated in co -operatives, however, cyber security risks are becoming increasingly prominent. Drons rely on data sharing to schedule task task, and this highly interacted communication mode means that an attack on a node can trigger a chain reaction throughout the network, similar to the risks faced by the hotel chain or supply chain network.
To address this challenge, a recent study conducted by a team of researchers from the School of Mathematical and Statistical Sciences of Arizona State University proposed a dynamic permission model. It is based on probable graph theory and spatial poison point processes, widely modeling the loss distribution of cyber security risks in various parameters of the drone delivery network.
By analyzing both single-layer and multi-layer models, the study evaluates the upper boundaries of damage to the drone flock and turret network under the study cybralac, which considers various system parameters such as signal strength, communication range and node vulgarity.
Simulation results indicate that with low network permission risks, defense resources can reduce adapted allocation of resources and better communication protocol losses; In contrast, in cases of high percolation probability, the loss increases.
especially, these findingspublished in Risk scienceNot only provides theoretical and practical support for cyber security risk assessment in drone distribution services, but also provides guidance to policy makers, risk management experts and cyber security professionals in optimization of defense strategies.
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Reference
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Original source url
https://doi.org/10.1016/j.risk.2024.100009
Money information
This work is funded by the National Science Foundation under the grant CNS-200792. The structures and numerical results presented in this work are produced by the joint invention of authors. This invention is pending.
About this Risk science
Risk science There is a common-onion magazine that publishes educational research and industry practices on risks and disruptive technologies in all fields including agriculture, economics, engineering, environmental science, finance, health, law, management, natural science, and public administration.
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