
@Article{cmc.2026.083828,
AUTHOR = {Kuldashbay Avazov, Kudratjon Zohirov, Alpamis Kutlimuratov, Charos Khidirova, Jasur Sevinov, Urishev Omadjon, Adilbek Dauletov, Akmalbek Abdusalomov, Young Im Cho},
TITLE = {Context-Aware Identity Validation for UAV-Assisted Urban Mobility and Traffic Monitoring Environments},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/cmc/online/detail/27435},
ISSN = {1546-2226},
ABSTRACT = {Unmanned aerial vehicles (UAVs) are becoming a common solution to urban mobility, and traffic monitoring as well, owing to their ability to be deployed flexibly, ability to see a broader area and real-time sensing. However, the reliability of UAV-assisted traffic systems can be compromised through identity spoofing, Sybil attacks, false data injection, and trajectory manipulation. Current authentication techniques primarily verify cryptographic identities but often cannot detect when a claimed identity is inconsistent with physical movement patterns and settings. To overcome this drawback, this paper presents a context-aware identity validation system, CIV-UAV, for UAV-based urban traffic surveillance. The paradigm combines a model of cryptographic validation, model mobility, on-the-fly visual, road-network, temporal continuity, anomaly scoring, and multi-UAV consensus into a cohesive trust-based validation model. The risk-adaptive policy also adjusts the validation strictness based on the seriousness of the situation and the level of uncertainty. The outcomes of simulations indicate that CIV-UAV enhances identity validation, lowers the false detection and false acceptance rates, and reinforces the detection of spoofing, Sybil behaviour, path forgery, injection of fake events, and vision-communication mismatch attacks. The suggested architecture provides an identity validation system that is easy to implement and can be upgraded to a next-generation UAV-intelligent transportation network.},
DOI = {10.32604/cmc.2026.083828}
}



