A high-performance malicious operation behavior detection model
Gaoda Wei, Mingxi Guan, Yunqiang Ma, Ruyin Sun, Wenhao Yuan, Youfeng Niu · 2022
While numerous security products, including data leakage prevention, have been added to corporate cybersecurity strategies, securing confidential data and assets remains a major challenge for businesses and organizations. According to a survey by a research institute in the United States, most of the most costly cybercrime cases are caused by theft by insiders, followed by DDoS and Web-based attacks. In this paper, the LightGBM algorithm is used, and the feature extraction uses the bag of words and the IF-IDF model to construct a malicious operation behavior detection model. By training with the classic SEA training set, the results show that our model is more than 97% accurate. And compared to the popular classification models, our model has higher performance.