A flexible SDN-based architecture for identifying and mitigating low-rate DDoS attacks using machine learning

JA Perez-Diaz, IA Valdovinos, KKR Choo, D Zhu - IEEE Access, 2020 - ieeexplore.ieee.org
While there have been extensive studies of denial of service (DoS) attacks and DDoS attack
mitigation, such attacks remain challenging to mitigate. For example, Low-Rate DDoS (LR …

Machine learning approaches for combating distributed denial of service attacks in modern networking environments

A Aljuhani - IEEE Access, 2021 - ieeexplore.ieee.org
A distributed denial of service (DDoS) attack represents a major threat to service providers.
More specifically, a DDoS attack aims to disrupt and deny services to legitimate users by …

Machine-learning-assisted security and privacy provisioning for edge computing: A survey

S Singh, R Sulthana, T Shewale… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Edge computing (EC), is a technological game changer that has the ability to connect
millions of sensors and provide services at the device end. The broad vision of EC integrates …

FMDADM: A multi-layer DDoS attack detection and mitigation framework using machine learning for stateful SDN-based IoT networks

WI Khedr, AE Gouda, ER Mohamed - IEEE Access, 2023 - ieeexplore.ieee.org
The absence of standards and the diverse nature of the Internet of Things (IoT) have made
security and privacy concerns more acute. Attacks such as distributed denial of service …

Denial of service attacks in edge computing layers: Taxonomy, vulnerabilities, threats and solutions

R Uddin, SAP Kumar, V Chamola - Ad Hoc Networks, 2024 - Elsevier
Edge computing has emerged as the dominant communication technology connecting IoT
and cloud, offering reduced latency and harnessing the potential of edge devices. However …

[HTML][HTML] A feedforward–convolutional neural network to detect low-rate dos in iot

HS Ilango, M Ma, R Su - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
The lack of standardization and the heterogeneous nature of the Internet of Things (IoT) has
exacerbated the issue of security and privacy. In literature, to improve security at the network …

An intelligent intrusion detection system for distributed denial of service attacks: A support vector machine with hybrid optimization algorithm based approach

S Sokkalingam, R Ramakrishnan - … and Computation: Practice …, 2022 - Wiley Online Library
Cloud computing offers comfortable service to business sectors as they can concentrate on
their products. Over the internet, cloud computing is liable to various security threats and …

IXP scrubber: learning from blackholing traffic for ML-driven DDoS detection at scale

M Wichtlhuber, E Strehle, D Kopp, L Prepens… - Proceedings of the …, 2022 - dl.acm.org
Distributed Denial of Service (DDoS) attacks are among the most critical cybersecurity
threats, jeopardizing the stability of even the largest networks and services. The existing …

MP-GUARD: A novel multi-pronged intrusion detection and mitigation framework for scalable SD-IOT networks using cooperative monitoring, ensemble learning, and …

A El-Sayed, W Said, A Tolba, Y Alginahi… - Computers and Electrical …, 2024 - Elsevier
The ever-increasing complexity of the Internet of Things (IoT) environment demands robust
and adaptable intrusion detection frameworks, as existing approaches struggle with real …

Distributed denial of service attack detection using naïve bayes and k-nearest neighbor for network forensics

AV Kachavimath, SV Nazare… - 2020 2nd International …, 2020 - ieeexplore.ieee.org
The detection of anomaly traffic has become one of the principal directions in the field of
network security intending to identify the attacks based on the specific deviations of the …