A Survey of DDOS Attacks Using Machine Learning Techniques

The DDoS attacks are the most destructive attacks that interrupt the safe operation of essential services delivered by the internet community’s different organizations. DDOS stands for Distributed Denial Of Service attacks. These attacks are becoming more complex and expected to expand in number day...

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Bibliographic Details
Published in:E3S web of conferences 2020-01, Vol.184, p.1052
Main Authors: Arshi, M, Nasreen, MD, Madhavi, Karanam
Format: Article
Language:English
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Summary:The DDoS attacks are the most destructive attacks that interrupt the safe operation of essential services delivered by the internet community’s different organizations. DDOS stands for Distributed Denial Of Service attacks. These attacks are becoming more complex and expected to expand in number day after day, rendering detecting and combating these threats challenging. Hence, an advanced intrusion detection system (IDS) is required to identify and recognize an- anomalous internet traffic behaviour. Within this article the process is supported on the latest dataset containing the current form of DDoS attacks including (HTTP flood, SIDDoS). This study combines well-known grouping methods such as Naïve Bayes, Multilayer Perceptron (MLP), and SVM, Decision trees.
ISSN:2267-1242
2267-1242
DOI:10.1051/e3sconf/202018401052