Drone Technology

15Network Intrusion Detection of Drones Using Recurrent Neural Networks

Yadala Sucharitha^1*, Pundru Chandra Shaker Reddy² and G. Suryanarayana³

¹ Department of Computer Science & Engineering, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India

² Department of Computer Science and Engineering Geethanjali College of Engineering and Technology, Hyderabad, Telangana, India

³ Department of Computer Science & Engineering, Vardhaman College of Engineering, Hyderabad, India

Abstract

Flying Ad Hoc Network (FANET) has obtained a great deal of interest over recent times because of their significant applications. Thus, various examinations have been led on working with FANET applications in different fields. FANET’s distinctive properties have made it intricate to reinforce its safeguard next to steadily varying security dangers. Nowadays, progressively more FANET appliances are carried out into common airspace, yet the enlargement of FANET protection has remained unacceptable. However, FANET’s unusual roles ended it intricate to help arising dangers, particularly interruption recognition. This research explores FANET intrusion-detection threats by presenting a real-time data-analytics structure utilizing on deep-learning. The system comprises of Recurrent-Neural-Networks (RNN) as a foundation. It likewise includes gathering information from the network and breaking down it utilizing enormous information examination for inconsistency discovery. The information assortment ...