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 …
Internet, disrupting the availability of essential services. The challenge of DDoS detection is …
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 …
services due to their size and frequency. However, developing an effective security …
A long short-term memory enabled framework for DDoS detection
The proliferation of attack-for-hire services, coupled with the advent of Internet of Things
(IoT)-enabled botnets, is driving the increase of the frequency and intensity of Distributed …
(IoT)-enabled botnets, is driving the increase of the frequency and intensity of Distributed …
DDoS intrusion detection through machine learning ensemble
Distributed Denial of Service (DDoS) attacks have been the prominent attacks over the last
decade. A Network Intrusion Detection System (NIDS) should seamlessly configure to fight …
decade. A Network Intrusion Detection System (NIDS) should seamlessly configure to fight …
Ae-mlp: A hybrid deep learning approach for ddos detection and classification
Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet
connectivity massively grows in recent years. Conventional shallow machine learning-based …
connectivity massively grows in recent years. Conventional shallow machine learning-based …
Ddos attacks detection with autoencoder
Although many distributed denial of service (DDoS) attacks detection algorithms have been
proposed and even some of them have claimed high detection accuracy, DDoS attacks are …
proposed and even some of them have claimed high detection accuracy, DDoS attacks are …
Deepdetect: detection of distributed denial of service attacks using deep learning
At the advent of advanced wireless technology and contemporary computing paradigms,
Distributed Denial of Service (DDoS) attacks on Web-based services have not only …
Distributed Denial of Service (DDoS) attacks on Web-based services have not only …
A deep learning based DDoS detection system in software-defined networking (SDN)
Distributed Denial of Service (DDoS) is one of the most prevalent attacks that an
organizational network infrastructure comes across nowadays. We propose a deep learning …
organizational network infrastructure comes across nowadays. We propose a deep learning …
An efficient counter-based DDoS attack detection framework leveraging software defined IoT (SD-IoT)
The Internet of things (IoT) introduces emerging applications (ie, smart homes, smart cities,
smart health, and smart gird) that assist the traditional infrastructure environments to be …
smart health, and smart gird) that assist the traditional infrastructure environments to be …
Deep learning approaches for detecting DDoS attacks: A systematic review
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 …
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …