中圖分類號： TP393
文獻標識碼： A
DOI： 10.19358/j.issn.2097-1788.2023.02.001
引用格式： 趙云澤，蔣牧秋，董偉，等. 基于雙層注意力機制的惡意URL檢測[J].網絡安全與數據治理，2023，42(2)：3-8.

Malicious URL detection based on double attention mechanism

Abstract： With the continuous development of information technology, threats in cyberspace are also changing. Among them, attacks based on malicious URLs keep intruding. In this paper, the problem of malicious URL identification and detection is deeply explored, and a Bi-LSTM network model with a two-layer attention mechanism is designed and implemented to identify and detect malicious URLs, which is named A2Bi-LSTM. This model calculates the attention weight value of suspicious content contained in malicious URLs at the character level and word level, which further improves the recognition accuracy of malicious URLs. The experimental results show that the identification accuracy of A2Bi-LSTM for malicious URLs reaches 97%, which is better than the traditional detection model, and it can effectively deal with such threats as well as help the construction of cyberspace security system.

Key words : malicious URLs；attention mechanism；cyber security；deep learning