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Attack based DoS attack detection using multiple classifier
[article]
2020
arXiv
pre-print
One of the most common internet attacks causing significant economic losses in recent years is the Denial of Service (DoS) flooding attack. As a countermeasure, intrusion detection systems equipped with machine learning classification algorithms were developed to detect anomalies in network traffic. These classification algorithms had varying degrees of success, depending on the type of DoS attack used. In this paper, we use an SNMP-MIB dataset from real testbed to explore the most prominent
arXiv:2001.05707v1
fatcat:wdd2xph43bdxlmfpdx7pq3nuxq