DDoS attacks and machine‐learning‐based detection methods: A survey and taxonomy

M Najafimehr, S Zarifzadeh, S Mostafavi - Engineering Reports, 2023 - Wiley Online Library
Distributed denial of service (DDoS) attacks represent a significant cybersecurity challenge,
posing a critical risk to computer networks. Develo** an effective defense mechanism …

A hybrid machine learning approach for detecting unprecedented DDoS attacks

M Najafimehr, S Zarifzadeh, S Mostafavi - The Journal of Supercomputing, 2022 - Springer
Abstract Service availability plays a vital role on computer networks, against which
Distributed Denial of Service (DDoS) attacks are an increasingly growing threat each year …

DDoS attack detection and classification via Convolutional Neural Network (CNN)

AR Shaaban, E Abd-Elwanis… - 2019 Ninth International …, 2019 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks became the most widely spread attack because
it is easily designed and executed but it is very difficult to detect and mitigate. Several …

Detection of DDoS attacks using machine learning classification algorithms

KB Dasari, N Devarakonda - International Journal of …, 2022 - search.proquest.com
The Internet is the most essential tool for communication in today's world. As a result, cyber-
attacks are growing more often, and the severity of the consequences has risen as well …

A hybrid approach for detection of ddos attacks using entropy and machine learning in software defined networks

A Yadav, AS Kori, P Shettar… - 2021 12th International …, 2021 - ieeexplore.ieee.org
Software-defined networking is one of the fast-growing and emerging technology which
separates the control plane from the data plane. The control plane enables global network …

[PDF][PDF] DDoS attack detection: Strategies, techniques, and future directions

S Shivaji - J. Electrical Systems, 2024 - researchgate.net
Distributed Denial of Service (DDoS) attacks represent one of the most significant threats to
network security, capable of causing widespread disruption to digital infrastructures. The …

A Review of Defense against Distributed DoS attack based on Artificial Intelligence Approaches

A Ali, A Chaudhary, S Sahana - 2021 IEEE 6th International …, 2021 - ieeexplore.ieee.org
Modern society is heavily reliant on information and communication technologies, which has
made it more vulnerable to a wide range of cyber-attacks in recent decades. A Distributed …

DDoS Attack Detection Using Predictive Machine Learning (ML) Algorithms in Wireless Body Area Network Environments

BT Welteji, B Tiwari, SD Kebede, S Gupta… - IoT in Healthcare …, 2023 - taylorfrancis.com
Wireless body area networks (WBANs) are one of the key technologies that support the
development of pervasive health monitoring (remote patient monitoring systems), which has …

DDoS Detection using Machine Learning Approach

RP Janivasya, IDA Rachmawati - Procedia Computer Science, 2024 - Elsevier
Abstract Distributed Denial of Service (DDoS) attacks pose a significant threat to online
services by flooding targets with unusually high volumes of traffic or data, disrupting services …

Comparative Study between Texture Feature and Local Feature Descriptors for Silk Fabric Pattern Image Recognition

T Khamket, O Surinta - Proceedings of the 3rd International Conference …, 2020 - dl.acm.org
Thai silk fabrics have unique patterns in different regions of Thailand. The designers may
have been inspired and took ideas from the natural environment to create new silk patterns …