Dataset of intrusion detection alerts from a sharing platform

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Authors	HUSÁK Martin ŽÁDNÍK Martin BARTOŠ Václav SOKOL Pavol
Year of publication	2020
Type	Article in Periodical
Magazine / Source	Data in Brief
MU Faculty or unit	Institute of Computer Science
Citation
Web	https://doi.org/10.1016/j.dib.2020.106530 https://www.sciencedirect.com/science/article/pii/S2352340920314128
Doi	http://dx.doi.org/10.1016/j.dib.2020.106530
Keywords	Cyber security;Intrusion detection alerts;Information exchange;Geolocation;Reputation
Description	The dataset contains intrusion detection alerts obtained via an alert sharing platform (SABU) for one week. A plethora of heterogeneous intrusion detection systems deployed across several organizations contributed to the sharing platform. The alerts are stored in the intrusion Detection Extensible Alert (IDEA) format and categorized using the eCSIRT.net Incident Taxonomy. Dataset can be used in several areas of cybersecurity research for the analysis of intrusion detection alerts including temporal and spatial correlations, reputation scoring, attack scenario reconstruction, and attack projection. The network identifiers (e.g., IP addresses, hostnames) are anonymized. However, the list of interesting features (e.g., presence on blacklists, geolocation) of such entities at the time of data collection is provided.
Related projects:	CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence