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Disclaimer:
This Resource is offered and provided outside of the IMPACT mediation framework. IMPACT and the IMPACT Coordination Council/Blackfire Technology, Inc. expressly disclaim all conditions, representations and warranties including but not limited to Resource availability, quality, accuracy, non-infringement, and non-interference. All Resource information and access is controlled by entities and under terms that are external to the IMPACT legal framework.
Summary
DS-1257
Anomaly Detection Dataset(CSE-CIC-IDS2018)
External Dataset
External Data Source
University of New Brunswick
Unknown
Unknown
56 (lowest rank is 56)
Description
This project developed a systematic approach to generate diverse and comprehensive benchmark datasets for intrusion detection resulting in a dataset containing multiple different attack scenarios.
The dataset includes seven different attack scenarios: Brute-force, Heartbleed, Botnet, DoS, DDoS, Web attacks, and infiltration of the network from inside. The attacking infrastructure includes 50 machines and the victim organization has 5 departments and includes 420 machines and 30 servers. The dataset includes the captures network traffic and system logs of each machine, along with 80 features extracted from the captured traffic.
Additional Details
N/A
false
Unknown
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