DDoS attack detection in IoT-based networks using machine learning models: a survey and research directions

AA Alahmadi, M Aljabri, F Alhaidari, DJ Alharthi… - Electronics, 2023 - mdpi.com
With the emergence of technology, the usage of IoT (Internet of Things) devices is said to be
increasing in people's lives. Such devices can benefit the average individual, who does not …

[HTML][HTML] Proposed algorithm for smart grid DDoS detection based on deep learning

SY Diaba, M Elmusrati - Neural Networks, 2023 - Elsevier
Abstract The Smart Grid's objective is to increase the electric grid's dependability, security,
and efficiency through extensive digital information and control technology deployment. As a …

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. Developing an effective defense mechanism …

An intelligent DDoS attack detection tree-based model using Gini index feature selection method

MA Bouke, A Abdullah, SH ALshatebi… - Microprocessors and …, 2023 - Elsevier
Cyber security has recently garnered enormous attention due to the popularity of the Internet
of Things (IoT), intelligent devices' rapid growth, and a vast number of real-life applications …

An investigation into the performances of the state-of-the-art machine learning approaches for various cyber-attack detection: A survey

T Ige, C Kiekintveld, A Piplai - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
In this research, we analyzed the suitability of each of the current state-of-the-art machine
learning models for various cyberattack detection from the past 5 years with a major …

A DDoS detection method based on feature engineering and machine learning in software-defined networks

Z Liu, Y Wang, F Feng, Y Liu, Z Li, Y Shan - Sensors, 2023 - mdpi.com
Distributed denial-of-service (DDoS) attacks pose a significant cybersecurity threat to
software-defined networks (SDNs). This paper proposes a feature-engineering-and machine …

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 …

Quantum computing and machine learning for cybersecurity: Distributed denial of service (DDoS) attack detection on smart micro-grid

D Said - Energies, 2023 - mdpi.com
Machine learning (ML) is efficiently disrupting and modernizing cities in terms of service
quality for mobility, security, robotics, healthcare, electricity, finance, etc. Despite their …

Application layer DDoS attack detection using cuckoo search algorithm-trained radial basis function

H Beitollahi, DM Sharif, M Fazeli - IEEE Access, 2022 - ieeexplore.ieee.org
In an application-layer distributed denial of service (App-DDoS) attack, zombie computers
bring down the victim server with valid requests. Intrusion detection systems (IDS) cannot …

An effective classification of DDoS attacks in a distributed network by adopting hierarchical machine learning and hyperparameters optimization techniques

S Dasari, R Kaluri - IEEE Access, 2024 - ieeexplore.ieee.org
Data privacy is essential in the financial sector to protect client's sensitive information,
prevent financial fraud, ensure regulatory compliance, and safeguard intellectual property. It …