Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications

This work empirically evaluates machine learning models on two imbalanced public datasets KDDCUP99 and Credit Card Fraud 2013. The method includes data preparation, model training, and evaluation, using an 80/20 train/test split. Models tested include eXtreme Gradient Boosting XGB, Multi Layer...

Microsoft LightGBM 安全漏洞

Microsoft LightGBM is a gradient boosting framework using a tree-based learning algorithm from Microsoft USA. A remote code execution vulnerability exists in Microsoft LightGBM. An attacker could exploit this vulnerability to execute arbitrary code on a system...