: The project has since evolved into CREMEv2 , which offers expanded capabilities for dataset collection and more complex attack scenarios. Technical Components
The CREME project provides a toolchain for the automatic collection of datasets used to train machine learning models for (IDS). Its primary goal is to generate realistic, labeled datasets by simulating various cyberattacks in a controlled environment. Context of the 2021 Archive CREMEnaPromo2021.7z
: Used for automating interactive applications during attack simulations. : The project has since evolved into CREMEv2
: A log parsing framework for processing system logs into structured data. and attack labels (e.g.
: These datasets typically contain traffic logs, system metrics, and attack labels (e.g., DDoS, Brute Force, Mirai) used by researchers to benchmark AI-driven security tools.