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Machine Learning for DDoS Detection by Edi Suwandi is a document available to read on EtoBox.

What is Machine Learning for DDoS Detection about?

The document proposes a DDoS attack detection method based on machine learning. It extracts features from normal and attack traffic and uses them to train a random forest model. It captures real DDoS attack packets using TFN2K and normal packets to compare and identify differences. Key differences in packet sequence numbers, source IPs, ports and identifiers are extracted for TCP, UDP and ICMP traffic. These features are then used to train and test the random forest model, achieving good detection rates for

Author

Edi Suwandi

Language

EN