Journal Article

A hybrid security system for drones based on ICMetric technology

Alheeti, Khattab M. Ali, Khaled Alarfaj, Fawaz, Alreshoodi, Mohammed, Almusallam, Naif, Al Dosary, Duaa

2023

Overview

Recently, the number of drones has increased, and drones’ illegal and malicious use has become prevalent. The dangerous and wasteful effects are substantial, and the probability of attacks is very high. Therefore, an anomaly detection and protection system are needed. This paper aims to design and implement an intelligent anomaly detection system for the security of unmanned aerial vehicles (UAVs)/drones. The proposed system is heavily based on utilizing ICMetric technology to exploit low-level device features for detection. This technology extracts the accelerometer and gyroscope sensors’ bias to create a unique number known as the ICMetric number. Hence, ICMetric numbers represent additional features integrated into the dataset used to detect drones. This study performs the classification using a deep neural network (DNN). The experimental results prove that the proposed system achieves high levels of detection and performance metrics.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Accelerometers / Aircraft / Analysis / Anomalies / Artificial neural networks / Behavior / Biology and Life Sciences / Communication / Computer and Information Sciences / Computer security / Cybersecurity / Datasets / Deep learning / Drone aircraft / Drone vehicles / Drones / Electronic security systems / Engineering and Technology / Feature extraction / Global positioning systems / GPS / Health aspects / Hybrid systems / Identification / Integrated circuits / Intrusion detection systems / Management / Microelectromechanical systems / Neural networks / Performance measurement / Probability / Safety and security measures / Security systems / Sensors / Social Sciences / Technology / Unmanned Aerial Devices / Unmanned aerial vehicles