Malware Dataset Annotation for Machine Learning-Based Threat Detection
TextClassification
Annotated and prepared malware-related datasets for supervised machine learning models aimed at detecting malicious software behavior. Tasks included labeling executable behavior logs, categorizing samples into benign or malicious classes, cleaning noisy data, and validating label accuracy. Applied data preprocessing techniques and feature extraction to improve model performance. Ensured high-quality annotations through consistency checks and verification procedures suitable for cybersecurity-focused ML training.
Annotated and prepared malware-related datasets for supervised machine learning models aimed at detecting malicious software behavior. Tasks included labeling executable behavior logs, categorizing samples into benign or malicious classes, cleaning noisy data, and validating label accuracy. Applied data preprocessing techniques and feature extraction to improve model performance. Ensured high-quality annotations through consistency checks and verification procedures suitable for cybersecurity-focused ML training.
2024 - Present