An intrusion detection system against DDoS attacks in IoT networks
In this paper, we present an Intrusion Detection System (IDS) using the hybridization of the
deep learning technique and the multi-objective optimization method for the detection of …
deep learning technique and the multi-objective optimization method for the detection of …
Towards effective detection of recent DDoS attacks: A deep learning approach
I Ortet Lopes, D Zou, FA Ruambo… - Security and …, 2021 - Wiley Online Library
Distributed Denial of Service (DDoS) is a predominant threat to the availability of online
services due to their size and frequency. However, developing an effective security …
services due to their size and frequency. However, developing an effective security …
Nfdlm: A lightweight network flow based deep learning model for ddos attack detection in iot domains
In the recent years, Distributed Denial of Service (DDoS) attacks on Internet of Things (IoT)
devices have become one of the prime concerns to Internet users around the world. One of …
devices have become one of the prime concerns to Internet users around the world. One of …
DDoS detection in 5G-enabled IoT networks using deep Kalman backpropagation neural network
Abstract The fifth-generation (5G) wireless communication systems associating with the high
achievable data-transfer speeds will significantly affect the performance of IoT networks. On …
achievable data-transfer speeds will significantly affect the performance of IoT networks. On …
An efficient approach to detect distributed denial of service attacks for software defined internet of things combining autoencoder and extreme gradient boosting with …
MA Setitra, M Fan… - Transactions on Emerging …, 2023 - Wiley Online Library
The growing popularity of Software Defined Networks (SDN) and the Internet of Things (IoT)
has led to the emergence of Software Defined Internet of Things (SDIoT) based on …
has led to the emergence of Software Defined Internet of Things (SDIoT) based on …
Anomaly Detection IDS for Detecting DoS Attacks in IoT Networks Based on Machine Learning Algorithms
E Altulaihan, MA Almaiah, A Aljughaiman - Sensors, 2024 - mdpi.com
Widespread and ever-increasing cybersecurity attacks against Internet of Things (IoT)
systems are causing a wide range of problems for individuals and organizations. The IoT is …
systems are causing a wide range of problems for individuals and organizations. The IoT is …
DI‐ADS: A Deep Intelligent Distributed Denial of Service Attack Detection Scheme for Fog‐Based IoT Applications
Nowadays, fog computing plays a very vital role in providing many services to end‐based
IoT (Internet of Things) systems. The end IoT devices communicate with the middle layer fog …
IoT (Internet of Things) systems. The end IoT devices communicate with the middle layer fog …
A lightweight multi-vector DDoS detection framework for IoT-enabled mobile health informatics systems using deep learning
AD Aguru, SB Erukala - Information Sciences, 2024 - Elsevier
The exponential growth in adopting Internet of Things (IoT) applications and services has
rendered IoT security an essential concern that must be handled promptly. Multi-vector …
rendered IoT security an essential concern that must be handled promptly. Multi-vector …
Multi‐objective‐based feature selection for DDoS attack detection in IoT networks
In this study, the authors propose a multi‐objective optimisation‐based feature selection
(FS) method for the detection of distributed denial of service (DDoS) attacks in an internet of …
(FS) method for the detection of distributed denial of service (DDoS) attacks in an internet of …
Exploratory Analysis on Current Application-Layer HTTP-Payload-Based DDoS Attack on Internet of Things (IoT) Devices
The Internet of Things (IoT) Security has newly become a major concern and important
research topic because it directly interacts with human users. Application-layer Distributed …
research topic because it directly interacts with human users. Application-layer Distributed …