CIC-AndMal-2020

The 'CIC-AndMal-2020' dataset is a benchmark for evaluating malware detection methods, containing a large-scale, high-dimensional collection of malware samples used to assess the performance of detection frameworks like MeLeMaD.

Papers using CIC-AndMal-2020 (2)

CAFE-GB: Scalable and Stable Feature Selection for Malware Detection via Chunk-wise Aggregated Gradient Boosting2026MeLeMaD: Adaptive Malware Detection via Chunk-wise Feature Selection and Meta-Learning2025