Intelligent intrusion detection system for a group of UAVs

Abstract

Today, the creation of UAV groups is becoming a very popular and relevant task. Nevertheless, the use of UAVs is not securely, since they are vulnerable not only to attacks by an intruder, but also to environmental influences. Thus, the occurrence of anomalies must be detected in time. This work is aimed at detecting anomalies in UAV groups and determining the type of attack. To accomplish this task, the authors have developed an experimental stand emulating traffic transmission in a UAV group. The study is based on the investigation of changes in traffic transmission patterns during normal operation and under attacks. Data sets for training a neural network were collected using an developed testbed