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Keywords

dron, UAV, axborot xavfsizligi, mashinali o‘qitish, SVM, CNN, RNN, LSTM.

How to Cite

DRONLARDA AXBOROT XAVFSIZLIGINI TA’MINLASHDA MASHINALI O‘QITISH ALGORITMLARIDAN FOYDALANISHNING SAMARADORLIGI. (2026). "XXI ASRDA INNOVATSION TEXNOLOGIYALAR, FAN VA TAʼLIM TARAQQIYOTIDAGI DOLZARB MUAMMOLAR" Nomli Respublika Ilmiy-Amaliy Konferensiyasi, 4(10), 101-103. https://www.universalpublishings.com/index.php/itfttdm/article/view/20911

Abstract

Dronlarga bo‘lgan ehtiyojning ortishi dron sanoatining  rivojlanishiga olib keldi. Dronlar geodeziya ishlari, xavfsizlik patruli, favqulodda  vaziyatlar, qishloq xo‘jaligi, xizmatlarning kundalik monitoringi va kuzatuv kabi  sohalarda keng qo‘llanilmoqda. Shu bilan birga dronlarni boshqarish ilovalari va aloqa  kanallariga hujumlar soni ham ko‘payib, xavfsizlikka bo‘lgan tahdidlar ortib  bormoqda. Dronlarda resurslar cheklangani sababli aloqani murakkab algoritmlar  yordamida shifrlash ideal yechim emas: katta hajmdagi ma’lumotlar almashinuvida  shifrlash ma’lum miqdorda hisoblash quvvatini talab qiladi. Shu bois aloqa kanallari  xavfsizligini ta’minlashda boshqacha yondashuv zarur bo‘lib, mashinali o‘qitish (ML  — Machine Learning) ana shunday yondashuvni taqdim etadi [1]. 

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References

1. Alvarado E. 237 Ways Drone Applications Revolutionize Business // Drone Industry Insights. 3 May 2021.

2. Bensalem M., Singh S. K., Jukan A. On detecting and preventing jamming attacks with machine learning in optical networks // 2019 IEEE Global Communications Conference (GLOBECOM). IEEE, 2019, pp. 1–6.

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