Dataset Open Access

Netflow data without sampling for training (D1)

Ignacio; Adrian


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    <subfield code="a">&lt;p&gt;NetFlow traffic generated using&amp;nbsp;&lt;strong&gt;DOROTHEA&lt;/strong&gt;&amp;nbsp;(&lt;strong&gt;DO&lt;/strong&gt;cker-based f&lt;strong&gt;R&lt;/strong&gt;amework f&lt;strong&gt;O&lt;/strong&gt;r ga&lt;strong&gt;TH&lt;/strong&gt;ering n&lt;strong&gt;E&lt;/strong&gt;tflow tr&lt;strong&gt;A&lt;/strong&gt;ffic)&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;

&lt;p&gt;NetFlow flows have been captured without sampling 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.&lt;/p&gt;

&lt;p&gt;The version of NetFlow used to build the datasets is 5.&lt;/p&gt;

&lt;p&gt;In the construction of the datasets, different percentages of flows considered attacks and flows considered normal traffic have been used.&lt;/p&gt;

&lt;p&gt;These datasets have been used to train machine learning models.&lt;/p&gt;</subfield>
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