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Distributed Denial of Service Attacks (DDoS)- Consequences and Future

, 2006
Denial of Service and the Distributed Denial of Service Attacks have recently emerged as one of the most newsworthy, if not the greatest, weaknesses of the Internet. This paper attempt to explain how they work, why they are hard to combat today, and what will need to happen if they are to be brought under control. It is divided into eight sections. The
openaire   +1 more source

New collaborative DDoS defense technology based on NFV

网络与信息安全学报, 2019
To solve the problem of selfish behavior for self-security due to limited resources in the process of resisting distributed denial of service (DDoS) attacks by a collaborative network built with network function virtualization (NFV) technology,a new ...
Chuanfeng XU, Hui LIN, Xuancheng GUO, Xiaoding WANG   +3 more
doaj  

Distributed Denial of Service (DDoS) Attack Mitigation using AI

International Journal for Research in Applied Science and Engineering Technology
Abstract: Distributed Denial of Service(DDoS) attacks have been the major threats for the Internet and can bring great loss to companies and governments. With the development of emergingtechnologies, suchascloudcomputing, InternetofThings(IoT), artificialintelligence techniques, attackers can launch a huge volume of DDoS attacks with a lower cost, and ...
openaire   +1 more source

Distributed denial-of-service (DDOS) attack detection using supervised machine learning algorithms. [PDF]

Sci Rep
Abiramasundari S, Ramaswamy V.
europepmc   +1 more source

Distributed denial of service (DDoS) classification based on random forest model with backward elimination algorithm and grid search algorithm. [PDF]

Sci Rep
Sawah MS, Elmannai H, El-Bary AA, Lotfy K, Sheta OE.   +4 more
europepmc   +1 more source

Distributed denial-of-service (DDoS) on the smart grids based on VGG19 deep neural network and Harris Hawks optimization algorithm. [PDF]

Sci Rep
Alhashmi A, Idwaib H, Avci SA, Rahebi J, Ghadami R.   +4 more
europepmc   +1 more source

Investigating the performance of multivariate LSTM models to predict the occurrence of Distributed Denial of Service (DDoS) attack. [PDF]

PLoS One
Kumar P, Kushwaha C, Sethi D, Ghosh D, Gupta P, Vidyarthi A.   +5 more
europepmc   +1 more source

Deep learning-based HTTP TRACE flood detection in wireless sensor network using deep spectral multi-layer convolutional neural network. [PDF]

Sci Rep
Tamilselvi S, Shieh CS, Horng MF, Shanker NR.   +3 more
europepmc   +1 more source

Ensemble-based detection of distributed denial-of-service attacks in IoT networks using majority decision mechanisms. [PDF]

Sci Rep
Cheng S, Feng X.
europepmc   +1 more source

Optimized CatBoost machine learning (OCML) for DDoS detection in cloud virtual machines with time-series and adversarial robustness. [PDF]

Sci Rep
Samy H, Bahaa-Eldin AM, Sobh MA, Taha A.
europepmc   +1 more source