Dataset Open Access

Netflow data without sampling for training (D1)

Ignacio; Adrian


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    "description": "<p>NetFlow traffic generated using&nbsp;<strong>DOROTHEA</strong>&nbsp;(<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)</p>\n\n<p>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.</p>\n\n<p>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.</p>\n\n<p>The version of NetFlow used to build the datasets is 5.</p>\n\n<p>In the construction of the datasets, different percentages of flows considered attacks and flows considered normal traffic have been used.</p>\n\n<p>These datasets have been used to train machine learning models.</p>", 
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    "title": "Netflow data without sampling for training (D1)", 
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    "keywords": [
      "NetFlow", 
      "Dataset", 
      "DOROTHEA", 
      "Network traffic", 
      "Network attacks"
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    "publication_date": "2020-10-19", 
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        "name": "Ignacio"
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Data volume 45.6 GB45.6 GB
Unique views 107107
Unique downloads 8888

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