[HTML][HTML] Predicting DoS and DDoS attacks in network security scenarios using a hybrid deep learning model

AF Al-zubidi, AK Farhan, SM Towfek - Journal of Intelligent Systems, 2024 - degruyter.com
Network security faces increasing threats from denial of service (DoS) and distributed denial
of service (DDoS) attacks. The current solutions have not been able to predict and mitigate …

Effective Intrusion Detection System Using Deep Learning for DDoS Attacks

J Shaikh, YA Butt, HF Naqvi - The Asian Bulletin of Big Data …, 2024 - abbdm.com
An increasing demand for information technology and cloud computing has led to various
security threats over internet. Amongst all types of threats, Distributed Denial of Service …

Intrusion detection for modern DDoS attacks classification based on convolutional neural networks

W Chen, H Zhang, X Zhou, Y Weng - International Conference on …, 2021 - Springer
Abstract Distributed Denial of Service (DDos) attack is one of the most harmful attacks
demonstrating its huge scale and enormous impact on people's daily life and also …

[PDF][PDF] RTL-DL: a hybrid deep learning framework for DDOS attack detection in a big data environment

HA Afolabi, AA Aburas - Int J Comput Netw Commun, 2022 - academia.edu
ABSTRACT A distributed denial of service (DDoS) attack is one of the most common cyber
threats to the Internet of Things (IoT). Several deep learning (DL) techniques have been …

Developing Realistic Distributed Denial of Service (DDoS) Dataset for Machine Learning-based Intrusion Detection System

HJ Hadi, U Hayat, N Musthaq… - 2022 9th International …, 2022 - ieeexplore.ieee.org
During the last decade, attackers have compromised reputable systems to launch massive
Distributed Denial of Services (DDoS) attacks against banking services, corporate websites …

Hybrid Approach to Classification of DDoS Attacks on a Computer Network Infrastructure

EQ Effah, EO Osei, A Tetteh - Asian Journal of Research …, 2024 - info.submit4journal.com
The advancement in technology, its ease of use, and the competitive nature of its
deployment in business operations have led to the wide spread of networking systems …

Detection of DDoS attacks with feed forward based deep neural network model

AE Cil, K Yildiz, A Buldu - Expert Systems with Applications, 2021 - Elsevier
As a result of the increase in the services provided over the internet, it is seen that the
network infrastructure is more exposed to cyber attacks. The most widely used of these …

A lightweight dos and ddos attack detection mechanism-based on deep learning

SP Satpathy, S Mohanty… - 2022 5th International …, 2022 - ieeexplore.ieee.org
Denial of Service (DOS) attacks are one of the major attacks on any network and a potential
threat to internet resources and services. This threat amplifies with Distributed Denial of …

An optimized neural network-based IDS against DDoS attacks

A Aouatif, B Omar, C Hakima - 2023 10th International …, 2023 - ieeexplore.ieee.org
As cyberattacks become increasingly sophisticated, the identification of harmful assaults like
Distributed Denial of Service (DDoS) poses a significant challenge. DDoS attacks have …

Towards DDoS attack detection using deep learning approach

S Aktar, AY Nur - Computers & Security, 2023 - Elsevier
Due to the extensive use and evolution in the cyber world, different network attacks have
recently increased significantly. Distributed Denial-of-Service (DDoS) attack has become …