Deep learning approaches for detecting DDoS attacks: A systematic review

M Mittal, K Kumar, S Behal - Soft computing, 2023 - Springer
In today's world, technology has become an inevitable part of human life. In fact, during the
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …

Machine learning techniques to detect a DDoS attack in SDN: A systematic review

TE Ali, YW Chong, S Manickam - Applied Sciences, 2023 - mdpi.com
The recent advancements in security approaches have significantly increased the ability to
identify and mitigate any type of threat or attack in any network infrastructure, such as a …

Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments

MP Novaes, LF Carvalho, J Lloret… - Future Generation …, 2021 - Elsevier
Over the last few years, Software Defined Networking (SDN) paradigm has become an
emerging architecture to design future networks and to meet new application demands. SDN …

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 …

SDN-based architecture for transport and application layer DDoS attack detection by using machine and deep learning

NM Yungaicela-Naula, C Vargas-Rosales… - IEEE …, 2021 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks represent the most common and critical attacks
targeting conventional and new generation networks, such as the Internet of Things (IoT) …

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 …

FLEAM: A federated learning empowered architecture to mitigate DDoS in industrial IoT

J Li, L Lyu, X Liu, X Zhang, X Lyu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Due to resource constraints and working surroundings, many IIoT nodes are easily hacked
and turn into zombies from which to launch attacks. It is challenging to detect such …

Vulnerability retrospection of security solutions for software-defined Cyber–Physical System against DDoS and IoT-DDoS attacks

M Snehi, A Bhandari - Computer Science Review, 2021 - Elsevier
The wide dispersion of the Internet of Things (IoT), Software-defined Networks and Cloud
Computing have given the wings to Cyber–Physical System adoption. The newfangled …

Long short-term memory and fuzzy logic for anomaly detection and mitigation in software-defined network environment

MP Novaes, LF Carvalho, J Lloret, ML Proença - IEEE Access, 2020 - ieeexplore.ieee.org
Computer networks become complex and dynamic structures. As a result of this fact, the
configuration and the managing of this whole structure is a challenging activity. Software …

A hybrid deep learning-driven SDN enabled mechanism for secure communication in Internet of Things (IoT)

D Javeed, T Gao, MT Khan, I Ahmad - Sensors, 2021 - mdpi.com
The Internet of Things (IoT) has emerged as a new technological world connecting billions of
devices. Despite providing several benefits, the heterogeneous nature and the extensive …