An efficient hybrid-dnn for ddos detection and classification in software-defined iiot networks

A Zainudin, LAC Ahakonye, R Akter… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Software-defined networking (SDN)-based Industrial Internet of Things (IIoT) networks have
a centralized controller that is a single attractive target for unauthorized users to attack …

[HTML][HTML] Security analysis of ddos attacks using machine learning algorithms in networks traffic

RJ Alzahrani, A Alzahrani - Electronics, 2021 - mdpi.com
The recent advance in information technology has created a new era named the Internet of
Things (IoT). This new technology allows objects (things) to be connected to the Internet …

[HTML][HTML] A novel multi algorithm approach to identify network anomalies in the IoT using Fog computing and a model to distinguish between IoT and Non-IoT devices

RJ Alzahrani, A Alzahrani - Journal of Sensor and Actuator Networks, 2023 - mdpi.com
Botnet attacks, such as DDoS, are one of the most common types of attacks in IoT networks.
A botnet is a collection of cooperated computing machines or Internet of Things gadgets that …

[HTML][HTML] ML-Based Traffic Classification in an SDN-Enabled Cloud Environment

O Belkadi, A Vulpe, Y Laaziz, S Halunga - Electronics, 2023 - mdpi.com
Traffic classification plays an essential role in network security and management; therefore,
studying traffic in emerging technologies can be useful in many ways. It can lead to …

Machine Learning Techniques for Detecting DDOS Attacks

MM Saeed, HNR Mohammed… - … on Emerging Smart …, 2023 - ieeexplore.ieee.org
The development witnessed by the world of science and technology and the emergence of
the Internet, where cybersecurity has become one of the most important areas that are …

A path selection scheme for detecting malicious behavior based on deep reinforcement learning in SDN/NFV-Enabled network

M Li, S Deng, H Zhou, Y Qin - Computer Networks, 2023 - Elsevier
The SDN/NFV network is prone to different types of attacks. The Distributed Denial of
Service (DDoS) attack has the most severe impact as it can overwhelm the critical …

Analysis of Machine Learning and Deep Learning Intrusion Detection System in Internet of Things Network*

S Rani, AK Bashir - … on Data Analytics for Business and …, 2022 - ieeexplore.ieee.org
As technology advances, more demands in various sectors rise, making everything smarter.
The Internet of Things (IoT) connects everything through an interconnected nodes also …

Method for filtering encrypted traffic using a neural network between an Industrial Internet of things system and Digital Twin

I Luksha, T Duy Dinh, E Karelin, R Glushakov… - Proceedings of the 5th …, 2021 - dl.acm.org
Several traffic optimization approaches are available nowadays, including compression,
packet deduplication, specialized hardware and software solutions, application optimization …

Effect Analysis of Malicious Flow Classification Model Based on Representation Learning on Network Flow Anomaly Detection

Y Hu, X Duan, Y Chen, Z Zhao - Information Technology and Control, 2024 - itc.ktu.lt
Network traffic anomaly detection, as a key link of network security, has been paid more and
more attention in recent years. Aiming at abnormal flow caused by improper network usage …

Comparative Evaluation on Various Machine Learning Strategies Based on Identification of DDoS Attacks in IoT Environment

M Abinaya, S Prabakeran… - 2023 9th International …, 2023 - ieeexplore.ieee.org
IoT is a combination of networks that have the ability to collect and share the information
through web. Though IoT is used in areas such as healthcare, smart cities, agriculture …