DDoS detection and prevention based on artificial intelligence techniques

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 emerging technologies, such as cloud computing, Internet of Things (IoT), artificial intelligence techniques, attackers can launch...

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Bibliographic Details
Published in:Scientific Bulletin ("Mircea cel Bătrân" Naval Academy) 2019-07, Vol.XXII (1), p.134-143
Main Authors: Glăvan, Dragoş, Răcuciu, Ciprian, Moinescu, Radu, Antonie, Narcis-Florentin
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Cloud computing
Denial of service attacks
Detection
Internet of Things
Machine learning
New technology
Prevention
Surveying
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Summary: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 emerging technologies, such as cloud computing, Internet of Things (IoT), artificial intelligence techniques, attackers can launch a huge volume of DDoS attacks with a lower cost, and it is much harder to detect and prevent DDoS attacks, because DDoS traffic is similar to normal traffic. Some artificial intelligence techniques like machine learning algorithms have been used to classify DDoS attack traffic and detect DDoS attacks, such as Naive Bayes and Random forest tree. In the paper, we survey on the latest progress on the DDoS attack detection using artificial intelligence techniques and give recommendations on artificial intelligence techniques to be used in DDoS attack detection and prevention.
ISSN:2392-8956
1454-864X
1454-864X
2392-8956
DOI:10.21279/1454-864X-19-I1-018