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 …

Efficient detection of DDoS attacks using a hybrid deep learning model with improved feature selection

D Alghazzawi, O Bamasag, H Ullah, MZ Asghar - Applied Sciences, 2021 - mdpi.com
DDoS (Distributed Denial of Service) attacks have now become a serious risk to the integrity
and confidentiality of computer networks and systems, which are essential assets in today's …

Towards effective detection of recent DDoS attacks: A deep learning approach

I Ortet Lopes, D Zou, FA Ruambo… - Security and …, 2021 - Wiley Online Library
Distributed Denial of Service (DDoS) is a predominant threat to the availability of online
services due to their size and frequency. However, developing an effective security …

A generalized machine learning model for DDoS attacks detection using hybrid feature selection and hyperparameter tuning

RK Batchu, H Seetha - Computer Networks, 2021 - Elsevier
In the digital era, the usage of network-connected devices is rapidly growing which leads to
an increase in cyberattacks. Among them, Distributed Denial of Service (DDoS) attacks are …

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 …

LUCID: A practical, lightweight deep learning solution for DDoS attack detection

R Doriguzzi-Corin, S Millar… - … on Network and …, 2020 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks are one of the most harmful threats in today's
Internet, disrupting the availability of essential services. The challenge of DDoS detection is …

Real-time DDoS attack detection system using big data approach

MJ Awan, U Farooq, HMA Babar, A Yasin, H Nobanee… - Sustainability, 2021 - mdpi.com
Currently, the Distributed Denial of Service (DDoS) attack has become rampant, and shows
up in various shapes and patterns, therefore it is not easy to detect and solve with previous …

A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking

AA Bahashwan, M Anbar, S Manickam, TA Al-Amiedy… - Sensors, 2023 - mdpi.com
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …

DDoS attack detection with feature engineering and machine learning: the framework and performance evaluation

M Aamir, SMA Zaidi - International Journal of Information Security, 2019 - Springer
This paper applies an organized flow of feature engineering and machine learning to detect
distributed denial-of-service (DDoS) attacks. Feature engineering has a focus to obtain the …