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Defending Airports from UAS: A Survey on Cyber-Attacks and Counter-Drone Sensing Technologies
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As the fastest growing segment of aviation, unmanned aerial systems (UAS) continue to increase in number, technical complexity and capabilities. Numerous civilian and commercial uses are drastically transforming civil protection, asset delivery, commercial and entertaining activities. However, UAS pose significant challenges in terms of safety, security and privacy within society. An increasing phenomenon, nowadays, is drone-related incidents near airport facilities, which are expected to proliferate in frequency, complexity and severity, as drones become larger and more powerful. Critical infrastructures need to be protected from such aerial attacks, through effective counteracting technologies, risk management and resilience plans. In this paper, we present a survey of drone incidents near airports and a literature review of sensor technologies, able to prevent, detect, identify and mitigate rogue drones. We exhibit the benefits and limitations of available counter-drone technologies (C-UAS); however, defending airports against misused drone activity is a hard problem. Therefore, we analyze three realistic attack scenarios from malicious drones and propose an effective C-UAS protection plan for each case. We discuss applicability limitations of C-UAS in the aviation context and propose a resilience action plan for airport stakeholders for defending against airborne threats from misused drones.
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“To prevent those misuses as in [150-154], counter-drone technology is widely under study, which for example, enables the configuration of guarded areas to either permit or block drones.”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [151]
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Metadata
- Authors
- Lykou, G., Moustakas, D., & Gritzalis, D.
- Affiliations
- Athens University of Economics and Business (GR)
- Corresponding author
- Gritzalis, Dimitris
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2020-06-22
- Volume
- 20
- Issue
- 12
- Pages
- 3537
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC7349857
- OpenAlex
- W3036046236
- Cited by
- 268
- References
- 78
- Citations by year
- 2026: 38 · 2025: 40 · 2024: 49 · 2023: 56 · 2022: 44 · 2021: 34 · 2020: 7
- FWCI
- 3.85
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
- Physical Sciences › Engineering › Aerospace Engineering › Air Traffic Management and Optimization
- Physical Sciences › Engineering › Aerospace Engineering › Military Technology and Strategies
- Keywords
- counter-UAS, unmanned aerial systems, airports, drone detection, drone identification, cyberattacks, critical infrastructure protection, attack scenarios, resilience planning, aviation security
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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