Benchmark
EMBER2024
A public benchmark dataset for malware classification that provides featurized PE file data. It is commonly used to evaluate the performance of machine learning models on security detection tasks.
Timeline (last 90 days)
Oct 22
On the three benchmarks UNSW-NB15, CIC-IDS2017, and EMBER2024, the paper compares against calibrated XGBoost, Random-Forest, MLP, and Kitsune, and measures a two-stage cascade of "Suricata (52,674 Emerging-Threats rules) → VX-One" running over five days on CIC-IDS2017.
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