TRA: Effective Authentication Mechanism for Swarms Of Unmanned Aerial Vehicles

التفاصيل البيبلوغرافية
العنوان: TRA: Effective Authentication Mechanism for Swarms Of Unmanned Aerial Vehicles
المؤلفون: Sergey Chuprov, Radda A. Iureva, Igor I. Komarov, Le Duy Don, Tran Duy Khanh
المصدر: SSCI
بيانات النشر: IEEE, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Authentication, Wireless network, Fire detection, business.industry, Computer science, Real-time computing, Swarm behaviour, ComputerApplications_COMPUTERSINOTHERSYSTEMS, 020206 networking & telecommunications, Ground control station, 02 engineering and technology, Drone, 0202 electrical engineering, electronic engineering, information engineering, Wireless, 020201 artificial intelligence & image processing, business, Wireless sensor network
الوصف: The swarm of the unmanned aerial vehicles is researched to meet the special mission requirements given both in the military and civilian sectors such as fire detection, sky reconnaissance, and other areas of human activities. These swarms can directly contact via ground control station or direct communication. However, when communicating remotely via wireless and fine maneuverability of the unmanned aerial vehicle, many mechanisms face several security gaps, such as the authentication mechanism in enemy attacks. In this study, we propose safe and effective authentication mechanism appropriate for the dynamic environment of the unmanned aerial vehicle. In the frames of this approach, a new operating mechanism in the proposed protocol is described. The protocol provides authentication security for swarms of the unmanned aerial vehicle. Our scheme allows good communication and computing performance as well as storage cost. Finally, simulation and results in the communication environment between drones are presented.
DOI: 10.1109/ssci47803.2020.9308140
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::3e2fced3feaf3669fe73cc99a8fbaf36
https://doi.org/10.1109/ssci47803.2020.9308140
Rights: CLOSED
رقم الانضمام: edsair.doi...........3e2fced3feaf3669fe73cc99a8fbaf36
قاعدة البيانات: OpenAIRE
الوصف
DOI:10.1109/ssci47803.2020.9308140