High-performance malicious program classification and identification model

Yixin Hong; Gaoda Wei; Yijing Sun; Yihang Li; Jingyi Yao; Runjiu Hu

doi:10.1117/12.2639878

19 October 2022 High-performance malicious program classification and identification model

Yixin Hong, Gaoda Wei, Yijing Sun, Yihang Li, Jingyi Yao, Runjiu Hu

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122945I (2022) https://doi.org/10.1117/12.2639878
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

Nowadays, Internet is an indispensable part of most people's life, but malicious programs always make people defensive. Malicious programs not only seriously affect people's daily experience, but also most likely threaten users' property security, or even directly threaten the normal operation of society. In this paper, we extract feature words by N-Gram model, further improve the classification performance by using TF-IDF algorithm, and train a high-performance malicious program classification and identification model by using LightGBM algorithm. Through experimental analysis, the accuracy rate of the model is over 96%. Compared with conventional classification models, the model has superior performance.

Citation Download Citation

Yixin Hong, Gaoda Wei, Yijing Sun, Yihang Li, Jingyi Yao, and Runjiu Hu "High-performance malicious program classification and identification model", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122945I (19 October 2022); https://doi.org/10.1117/12.2639878

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