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Ð’ результате иÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±Ñ‹Ð»Ð¸ раÑÑмотрены БПЛРгражданÑкого назначениÑ, их Ñферы применениÑ, конÑтруктивные оÑобенноÑти и ÑоÑтав аппаратуры. Также были перечиÑлены оÑновные рабочие чаÑтоты БПЛРгражданÑкого назначениÑ, их отличиÑ, преимущеÑтва и недоÑтатки. Приведен перечень вероÑтных видов атак Ñ Ð¾Ð¿Ð¸Ñанием принципов дейÑÑ‚Ð²Ð¸Ñ Ð¸ потенциальными поÑледÑтвиÑми, а также возможные методики борьбы Ñ Ð¿Ð¾Ð´Ð¾Ð±Ð½Ñ‹Ð¼Ð¸ атаками Ñ Ð¸Ñпользованием передовых на данный момент технологий. Результатом работы ÑвлÑетÑÑ ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑный обзор Ñферы БПЛРгражданÑкого назначениÑ, их потенциальные уÑзвимоÑти и методики борьбы Ñ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ñ‹Ð¼Ð¸ атаками Ñ Ñ†ÐµÐ»ÑŒÑŽ ÑƒÐ»ÑƒÑ‡ÑˆÐµÐ½Ð¸Ñ Ð¸Ñ… информационной безопаÑноÑти.
The given work is devoted to the consideration of the main types of civilian UAVs, possible vulnerabilities in their information security and to suggest ways to deal with probable types of attacks. As a result of the study, civilian UAVs, their scope, design features and equipment composition were considered. The main operating frequencies of civilian UAVs, their differences, advantages and disadvantages were also listed. A list of probable types of attacks is given with a description of the principles of action and potential consequences, as well as possible methods for combating such attacks using currently advanced technologies. The result of the work is a comprehensive overview of the scope of civilian UAVs, their potential vulnerabilities and methods of dealing with possible attacks in order to improve their information security.
blockchain, джаммеÑ, roll, gps spoofing, блокÑейн, drone, дÑон, air taxi, jammer, flight controller, подмена gps, lidar, pitch, Ñангаж, лидаÑ, yaw, fpv, кÑен, полеÑнÑй конÑÑоллеÑ, аÑака mitm, sdn, machine learning, mitm attack, аÑÑоÑакÑи, маÑинное обÑÑение, ÑÑманнÑе вÑÑиÑлениÑ, fog computing, ÑÑÑкание
blockchain, джаммеÑ, roll, gps spoofing, блокÑейн, drone, дÑон, air taxi, jammer, flight controller, подмена gps, lidar, pitch, Ñангаж, лидаÑ, yaw, fpv, кÑен, полеÑнÑй конÑÑоллеÑ, аÑака mitm, sdn, machine learning, mitm attack, аÑÑоÑакÑи, маÑинное обÑÑение, ÑÑманнÑе вÑÑиÑлениÑ, fog computing, ÑÑÑкание
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influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |