Machine Learning: Models, Challenges, and Research Directions
T Talaei Khoei, N Kaabouch - Future Internet, 2023 - mdpi.com
Machine learning techniques have emerged as a transformative force, revolutionizing
various application domains, particularly cybersecurity. The development of optimal …
various application domains, particularly cybersecurity. The development of optimal …
Cyber security in smart agriculture: Threat types, current status, and future trends
Smart agriculture (SA), which combines the Internet of Things (IoT) with a variety of smart
devices including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs) …
devices including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs) …
A comparative analysis of supervised and unsupervised models for detecting attacks on the intrusion detection systems
T Talaei Khoei, N Kaabouch - Information, 2023 - mdpi.com
Intrusion Detection Systems are expected to detect and prevent malicious activities in a
network, such as a smart grid. However, they are the main systems targeted by cyber …
network, such as a smart grid. However, they are the main systems targeted by cyber …
Supervised deep learning models for detecting GPS spoofing attacks on unmanned aerial vehicles
Unmanned Aerial Networks (UAVs) are prone to several cyber-atttacks, including Global
Positioining Spoofing attacks. For this purpose, numerous studies have been conducted to …
Positioining Spoofing attacks. For this purpose, numerous studies have been conducted to …
[HTML][HTML] Detection of GPS Spoofing Attacks in UAVs Based on Adversarial Machine Learning Model
L Alhoraibi, D Alghazzawi, R Alhebshi - Sensors, 2024 - mdpi.com
Advancements in wireless communication and automation have revolutionized mobility
systems, notably through autonomous vehicles and unmanned aerial vehicles (UAVs). UAV …
systems, notably through autonomous vehicles and unmanned aerial vehicles (UAVs). UAV …
DroneGuard: An Explainable and Efficient Machine Learning Framework for Intrusion Detection in Drone Networks
Vulnerabilities in drone networks stem from the reliance on GPS and wireless
communication technologies, combined with the lack of robust security mechanisms. This …
communication technologies, combined with the lack of robust security mechanisms. This …
Detecting message spoofing attacks on smart vehicles
The rapid proliferation of smart vehicles, particularly connected vehicles, has led to a rise in
cyberthreats. Ensuring the security of associated equipment has become a pressing …
cyberthreats. Ensuring the security of associated equipment has become a pressing …
Enhancing Drone Security Through Multi-Sensor Anomaly Detection and Machine Learning
MY Alzahrani - SN Computer Science, 2024 - Springer
Abstract Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, have
determined numerous applications across industries, ranging from aerial surveillance to …
determined numerous applications across industries, ranging from aerial surveillance to …
A Comparative Assessment of Unsupervised Deep Learning Models for Detecting GPS Spoofing Attacks on Unmanned Aerial Systems
TT Khoei, K Al Shamaileh… - 2024 Integrated …, 2024 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAV) are prone to cyber threats, including Global Positioning
System (GPS) spoofing attacks. Several studies have been performed to detect and classify …
System (GPS) spoofing attacks. Several studies have been performed to detect and classify …
Detecting Injection Attacks in ADS-B Devices Using RNN-Based Models
The Automatic Dependent Surveillance Broadcast (ADS-B) system is a critical
communication and surveillance technology used in the Next Generation (NextGen) project …
communication and surveillance technology used in the Next Generation (NextGen) project …