Dataset for An Automatic Unsupervised Complex Event Processing Rules Generation Architecture for Real-Time IoT Attacks Detection

Published: 17 January 2023| Version 1 | DOI: 10.17632/pzhm3jnw6w.1
Contributor:
José Roldán

Description

Dataset used to perform the experiments of the article "An Automatic Unsupervised Complex Event Processing Rules Generation Architecture for Real-Time IoT Attacks Detection". The distribution between training and testing is as follows: Normal: 50% training, 50% testing Subscription fuzzing: 80% training, 20% testing Disconnection wave: 15%training, 85% testing TCP SYN Scan: 10% training, 90% testing UDP port Scan: 10% training, 90% testing XMAS Scan: 10% training, 90% testing Telnet Connection: 10% training, 90% testing

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Institutions

Universidad de Castilla-La Mancha

Categories

Cybersecurity

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