A secure intrusion detection platform using blockchain and radial basis function neural networks for internet of drones
A Heidari, NJ Navimipour… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The Internet of Drones (IoD) is built on the Internet of Things (IoT) by replacing “Things” with
“Drones” while retaining incomparable features. Because of its vital applications, IoD …
“Drones” while retaining incomparable features. Because of its vital applications, IoD …
Machine learning for enhancing transportation security: A comprehensive analysis of electric and flying vehicle systems
H Alqahtani, G Kumar - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
This paper delves into the transformative role of machine learning (ML) techniques in
revolutionizing the security of electric and flying vehicles (EnFVs). By exploring key domains …
revolutionizing the security of electric and flying vehicles (EnFVs). By exploring key domains …
[HTML][HTML] Sea turtle foraging algorithm with hybrid deep learning-based intrusion detection for the internet of drones environment
Abstract The Internet of Drones (IoD) allows for coordinated control of airspace for
Unmanned Aerial Vehicles (UAVs), also known as drones. The decreasing costs of …
Unmanned Aerial Vehicles (UAVs), also known as drones. The decreasing costs of …
Deep Neural Networks meet computation offloading in mobile edge networks: Applications, taxonomy, and open issues
Abstract Mobile Edge Computing (MEC) is a modern paradigm that involves moving
computing and storage resources closer to the network edge, reducing latency, and …
computing and storage resources closer to the network edge, reducing latency, and …
[HTML][HTML] Early Intrusion Detection System using honeypot for industrial control networks
Abstract Man-in-the-Middle (MITM) and Distributed Denial of Service (DDoS) attacks are
significant threats, especially to Industrial Control Systems (ICS). The honeypot is one of the …
significant threats, especially to Industrial Control Systems (ICS). The honeypot is one of the …
Fast and accurate classifying model for denial-of-service attacks by using machine learning
A denial of service (DoS) attack is one of the dangerous threats to networks that Internet
resources and services will be less available, as they are easily operated and difficult to …
resources and services will be less available, as they are easily operated and difficult to …
Artificial intelligence (AI) advancements for transportation security: in-depth insights into electric and aerial vehicle systems
The transformative advancements in transportation technology have brought forth electric
and aerial vehicles (EnAVs) as revolutionizing modes of mobility. However, amidst the …
and aerial vehicles (EnAVs) as revolutionizing modes of mobility. However, amidst the …
A novel intrusion detection system based on artificial neural network and genetic algorithm with a new dimensionality reduction technique for UAV communication
Unmanned aerial vehicles (UAVs) are increasingly being deployed in crucial missions for
the armed forces, law enforcement, industrial control monitoring, and other sectors …
the armed forces, law enforcement, industrial control monitoring, and other sectors …
A Q-learning-based two-layer cooperative intrusion detection for internet of drones system
M Wu, Z Zhu, Y Xia, Z Yan, X Zhu, N Ye - Drones, 2023 - mdpi.com
The integration of unmanned aerial vehicles (UAVs) and the Internet of Things (IoT) has
opened up new possibilities in various industries. However, with the increasing number of …
opened up new possibilities in various industries. However, with the increasing number of …
Intrusion Detection System Using Machine Learning
A Kiran, SW Prakash, BA Kumar… - 2023 International …, 2023 - ieeexplore.ieee.org
The use of computers and the internet has spread rapidly over the course of the past few
decades. Every day, more and more people are coming to rely heavily on the internet. When …
decades. Every day, more and more people are coming to rely heavily on the internet. When …