A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports is a paper by Domenico Pascarella, Gabriella Gigante, Angela Vozella, Pierre Bieber, Thomas Dubot, Edgar Martinavarro, Giovanni Barraco, and Greta Li Calzi.

The expansion of drones necessitates careful consideration due to their potential as a menace in cases of negligent, illicit, or non-cooperative use. In the context of airports, it is crucial to establish a comprehensive protection system against drone intrusions, aiming to prevent airport closures. This system should incorporate an intrusion management system that employs proper risk assessment methodologies specifically designed for airport operations. These methodologies should explicitly address the characteristics of drone intrusions, potentially quantifying the risks involved. This research introduces a methodological framework for assessing the risks associated with drone intrusions in airports. The framework takes into account the unique features of drone intrusions, airport characteristics, and ongoing operations, considering both safety and security aspects. The approach combines model-based and data-driven techniques to accomplish the following objectives: (i) estimate an airport vulnerability index, quantifying the susceptibility of the airport to drone intrusions using reference datasets; (ii) define a set of event trees to evaluate the risks associated with various threat scenarios linked to drone intrusions. The proposed methodological framework is applied to a practical Milan Malpensa airport case study. The results demonstrate the approach’s effectiveness and highlight additional requirements for implementing counter-drone systems in airports based on the assessed risks.

Publication Date: November 2022

A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports contains the following major sections:

  • Introduction
  • Related Work
  • Risk Assessment Framework for Drone Intrusions at Airports
  • Airport Vulnerability Assessment
  • Event Tree Analysis
  • Case Study
  • Discussion
  • Conclusions

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Authors: Domenico Pascarella, Gabriella Gigante, Angela Vozella, Pierre Bieber,Thomas Dubot, Edgar Martinavarro, Giovanni Barraco, and Greta Li Calzi.

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