Netflow data with sampling for training (D2)

NetFlow traffic generated using <strong>DOROTHEA</strong> (<strong>DO</strong>cker-based f<strong>R</strong>amework f<strong>O</strong>r ga<strong>TH</strong>ering n<strong>E</strong>tflow tr<strong>A</strong>ffic) NetFlow is a network protocol developed by Cisco for the collection and monitoring of network traffic flow data generated. A flow is defined as a unidirectional sequence of packets with some common properties that pass through a network device. NetFlow flows have been captured with sampling 1000 at the packet level. A sampling means that 1 out of every X packets is selected to be flow while the rest of the packets are not valued. The version of NetFlow used to build the datasets is 5. In the construction of the datasets, different percentages of flows considered attacks and flows considered normal traffic have been used. These datasets have been used to train machine learning models.