UAV-NIDD: A Dynamic Dataset for Cybersecurity and Intrusion Detection in UAV Networks Article Swipe
Hassan Jalil Hadi
,
Yue Cao
,
Muhammad Khurram Khan
,
Naveed Ahmad
,
Yulin Hu
,
Chaowei Fu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/tnse.2025.3553442
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/tnse.2025.3553442
Unmanned Aerial Vehicles (UAVs) are necessary for numerous tasks but are vulnerable to cyber threats due to their widespread use and connectivity. The lack of a comprehensive dataset necessitates the development of effective detection and mitigation solutions. Our work introduces UAV-NIDD, a new dataset that addresses the gaps in understanding and countering both cyber and physical threats in UAV networks. It includes three distinct attack scenarios: compromised UAV initiating a network-wide attack, access point compromised network-wide intrusion, and compromised Ground Control Station (GCS) establishing a network-wide attack. We develop a real-time testbed for creating UAV-NIDD (Unmanned Aerial Vehicles-Network Intrusion Detection Dataset), incorporating UAV devices, data collection tools, and controllers. Our testbed facilitates cyberattack execution and data gathering under normal and attack conditions. Our dataset covers various cyber-attacks like Scanning, Reconnaissance, DoS, DDoS, GPS Jamming & Spoofing, MITM, Replay, Evil Twin, Brute-Force, and Fake Landing packet attacks. Additionally, UAV-NIDD presents a valuable resource for AI and ML solutions, strengthening UAV networks against evolving cyber threats. Moreover, we offer open access and cooperative innovation in terms of long-term updating of dataset.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tnse.2025.3553442
- OA Status
- green
- Cited By
- 3
- References
- 27
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4408790769Canonical identifier for this work in OpenAlex
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https://doi.org/10.1109/tnse.2025.3553442Digital Object Identifier
- Title
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UAV-NIDD: A Dynamic Dataset for Cybersecurity and Intrusion Detection in UAV NetworksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-03-24Full publication date if available
- Authors
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Hassan Jalil Hadi, Yue Cao, Muhammad Khurram Khan, Naveed Ahmad, Yulin Hu, Chaowei FuList of authors in order
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https://doi.org/10.1109/tnse.2025.3553442Publisher landing page
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YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1109/TNSE.2025.3553442Direct OA link when available
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Computer science, Intrusion detection system, Computer security, Intrusion, Malware, Intrusion prevention system, Real-time computing, Geology, GeochemistryTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| publication_date | 2025-03-24 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W4321793432, https://openalex.org/W4403599283, https://openalex.org/W4312576847, https://openalex.org/W4392719484, https://openalex.org/W4386320403, https://openalex.org/W4226217351, https://openalex.org/W4401878927, https://openalex.org/W4396920681, https://openalex.org/W4399851502, https://openalex.org/W3205985117, https://openalex.org/W1952056635, https://openalex.org/W2789828921, https://openalex.org/W6847209443, https://openalex.org/W2296509296, https://openalex.org/W4361010174, https://openalex.org/W3022604549, https://openalex.org/W3179240416, https://openalex.org/W3096448935, https://openalex.org/W6964071089, https://openalex.org/W4392254950, https://openalex.org/W3008603700, https://openalex.org/W3127172626, https://openalex.org/W3088058100, https://openalex.org/W3133786451, https://openalex.org/W7066667914, https://openalex.org/W2791315675, https://openalex.org/W4390044127 |
| referenced_works_count | 27 |
| abstract_inverted_index.a | 25, 41, 69, 84, 89, 149 |
| abstract_inverted_index.AI | 153 |
| abstract_inverted_index.It | 60 |
| abstract_inverted_index.ML | 155 |
| abstract_inverted_index.We | 87 |
| abstract_inverted_index.in | 48, 57, 172 |
| abstract_inverted_index.of | 24, 31, 174, 177 |
| abstract_inverted_index.to | 12, 16 |
| abstract_inverted_index.we | 165 |
| abstract_inverted_index.GPS | 132 |
| abstract_inverted_index.Our | 37, 109, 122 |
| abstract_inverted_index.The | 22 |
| abstract_inverted_index.UAV | 58, 67, 102, 158 |
| abstract_inverted_index.and | 20, 34, 50, 54, 77, 107, 114, 119, 141, 154, 169 |
| abstract_inverted_index.are | 4, 10 |
| abstract_inverted_index.but | 9 |
| abstract_inverted_index.due | 15 |
| abstract_inverted_index.for | 6, 92, 152 |
| abstract_inverted_index.new | 42 |
| abstract_inverted_index.the | 29, 46 |
| abstract_inverted_index.use | 19 |
| abstract_inverted_index.DoS, | 130 |
| abstract_inverted_index.Evil | 138 |
| abstract_inverted_index.Fake | 142 |
| abstract_inverted_index.both | 52 |
| abstract_inverted_index.data | 104, 115 |
| abstract_inverted_index.gaps | 47 |
| abstract_inverted_index.lack | 23 |
| abstract_inverted_index.like | 127 |
| abstract_inverted_index.open | 167 |
| abstract_inverted_index.that | 44 |
| abstract_inverted_index.work | 38 |
| abstract_inverted_index.& | 134 |
| abstract_inverted_index.(GCS) | 82 |
| abstract_inverted_index.DDoS, | 131 |
| abstract_inverted_index.MITM, | 136 |
| abstract_inverted_index.Twin, | 139 |
| abstract_inverted_index.cyber | 13, 53, 162 |
| abstract_inverted_index.offer | 166 |
| abstract_inverted_index.point | 73 |
| abstract_inverted_index.tasks | 8 |
| abstract_inverted_index.terms | 173 |
| abstract_inverted_index.their | 17 |
| abstract_inverted_index.three | 62 |
| abstract_inverted_index.under | 117 |
| abstract_inverted_index.(UAVs) | 3 |
| abstract_inverted_index.Aerial | 1, 96 |
| abstract_inverted_index.Ground | 79 |
| abstract_inverted_index.access | 72, 168 |
| abstract_inverted_index.attack | 64, 120 |
| abstract_inverted_index.covers | 124 |
| abstract_inverted_index.normal | 118 |
| abstract_inverted_index.packet | 144 |
| abstract_inverted_index.tools, | 106 |
| abstract_inverted_index.Control | 80 |
| abstract_inverted_index.Jamming | 133 |
| abstract_inverted_index.Landing | 143 |
| abstract_inverted_index.Replay, | 137 |
| abstract_inverted_index.Station | 81 |
| abstract_inverted_index.against | 160 |
| abstract_inverted_index.attack, | 71 |
| abstract_inverted_index.attack. | 86 |
| abstract_inverted_index.dataset | 27, 43, 123 |
| abstract_inverted_index.develop | 88 |
| abstract_inverted_index.testbed | 91, 110 |
| abstract_inverted_index.threats | 14, 56 |
| abstract_inverted_index.various | 125 |
| abstract_inverted_index.UAV-NIDD | 94, 147 |
| abstract_inverted_index.Vehicles | 2 |
| abstract_inverted_index.attacks. | 145 |
| abstract_inverted_index.creating | 93 |
| abstract_inverted_index.devices, | 103 |
| abstract_inverted_index.distinct | 63 |
| abstract_inverted_index.evolving | 161 |
| abstract_inverted_index.includes | 61 |
| abstract_inverted_index.networks | 159 |
| abstract_inverted_index.numerous | 7 |
| abstract_inverted_index.physical | 55 |
| abstract_inverted_index.presents | 148 |
| abstract_inverted_index.resource | 151 |
| abstract_inverted_index.threats. | 163 |
| abstract_inverted_index.updating | 176 |
| abstract_inverted_index.valuable | 150 |
| abstract_inverted_index.(Unmanned | 95 |
| abstract_inverted_index.Dataset), | 100 |
| abstract_inverted_index.Detection | 99 |
| abstract_inverted_index.Intrusion | 98 |
| abstract_inverted_index.Moreover, | 164 |
| abstract_inverted_index.Scanning, | 128 |
| abstract_inverted_index.Spoofing, | 135 |
| abstract_inverted_index.UAV-NIDD, | 40 |
| abstract_inverted_index.addresses | 45 |
| abstract_inverted_index.detection | 33 |
| abstract_inverted_index.effective | 32 |
| abstract_inverted_index.execution | 113 |
| abstract_inverted_index.gathering | 116 |
| abstract_inverted_index.long-term | 175 |
| abstract_inverted_index.necessary | 5 |
| abstract_inverted_index.networks. | 59 |
| abstract_inverted_index.real-time | 90 |
| abstract_inverted_index.collection | 105 |
| abstract_inverted_index.countering | 51 |
| abstract_inverted_index.initiating | 68 |
| abstract_inverted_index.innovation | 171 |
| abstract_inverted_index.introduces | 39 |
| abstract_inverted_index.intrusion, | 76 |
| abstract_inverted_index.mitigation | 35 |
| abstract_inverted_index.scenarios: | 65 |
| abstract_inverted_index.solutions, | 156 |
| abstract_inverted_index.solutions. | 36 |
| abstract_inverted_index.vulnerable | 11 |
| abstract_inverted_index.widespread | 18 |
| abstract_inverted_index.compromised | 66, 74, 78 |
| abstract_inverted_index.conditions. | 121 |
| abstract_inverted_index.cooperative | 170 |
| abstract_inverted_index.cyberattack | 112 |
| abstract_inverted_index.development | 30 |
| abstract_inverted_index.facilitates | 111 |
| abstract_inverted_index.Brute-Force, | 140 |
| abstract_inverted_index.controllers. | 108 |
| abstract_inverted_index.establishing | 83 |
| abstract_inverted_index.necessitates | 28 |
| abstract_inverted_index.network-wide | 70, 75, 85 |
| abstract_inverted_index.Additionally, | 146 |
| abstract_inverted_index.comprehensive | 26 |
| abstract_inverted_index.connectivity. | 21 |
| abstract_inverted_index.cyber-attacks | 126 |
| abstract_inverted_index.incorporating | 101 |
| abstract_inverted_index.strengthening | 157 |
| abstract_inverted_index.understanding | 49 |
| abstract_inverted_index.Reconnaissance, | 129 |
| abstract_inverted_index.Vehicles-Network | 97 |
| abstract_inverted_index.<p>Unmanned | 0 |
| abstract_inverted_index.dataset.</p> | 178 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.9658241 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |