A high-performance malicious operation behavior detection model

Gaoda Wei; Mingxi Guan; Yunqiang Ma; Ruyin Sun; Wenhao Yuan; Youfeng Niu

doi:10.1117/12.2646644

23 August 2022 A high-performance malicious operation behavior detection model

Gaoda Wei, Mingxi Guan, Yunqiang Ma, Ruyin Sun, Wenhao Yuan, Youfeng Niu

Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 123301I (2022) https://doi.org/10.1117/12.2646644
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China

Abstract

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.

Citation Download Citation

Gaoda Wei, Mingxi Guan, Yunqiang Ma, Ruyin Sun, Wenhao Yuan, and Youfeng Niu "A high-performance malicious operation behavior detection model", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 123301I (23 August 2022); https://doi.org/10.1117/12.2646644

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