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A Realistic Cyber Defense Dataset (CSE-CIC-IDS2018)

cyber security internet intrusion detection network traffic


This dataset is the result of a collaborative project between the Communications Security Establishment (CSE) and The Canadian Institute for Cybersecurity (CIC) that use the notion of profiles to generate cybersecurity dataset in a systematic manner. It incluides a detailed description of intrusions along with abstract distribution models for applications, protocols, or lower level network entities. The dataset includes seven different attack scenarios, namely 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 includes 420 PCs and 30 servers. This dataset includes the network traffic and log files of each machine from the victim side, along with 80 network traffic features extracted from captured traffic using CICFlowMeter-V3. For more information on the creation of this dataset, see this paper by researchers at the Canadian Institute for Cybersecurity (CIC) and the University of New Brunswick (UNB): Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization.

Update Frequency




Managed By

Canadian Institute for Cybersecurity

See all datasets managed by Canadian Institute for Cybersecurity.


How to Cite

A Realistic Cyber Defense Dataset (CSE-CIC-IDS2018) was accessed on DATE from

Resources on AWS

  • Description
    Network traffic and log files
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    AWS Region
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://cse-cic-ids2018/

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