Phishing URL recognition based on ordered neurons long short-term memory neural network and attention mechanism feature fusion

Qiaojuan Jia; Ming Liu; Xiaoyu Jin; Dawei Ma

doi:10.1117/12.2681573

1 June 2023 Phishing URL recognition based on ordered neurons long short-term memory neural network and attention mechanism feature fusion

Qiaojuan Jia, Ming Liu, Xiaoyu Jin, Dawei Ma

Author Affiliations +

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127181C (2023) https://doi.org/10.1117/12.2681573
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

Aiming at the increasingly serious problems of phishing websites and the poor characteristics of identifying phishing URL, a phishing URL recognition model based onordered neurons long short-term memory neural network( ON-LSTM) and attention mechanism feature fusion is proposed. Firstly, the URL is divided based on the word level and character level of sensitive words and special characters, and then the URL vector after word segmentation is input into the onlstm model to realize feature extraction. In order to enrich the feature information, the feature fusion layer adopts the feature splicing method to fuse the features of sensitive word level and character level, and introduces the attention mechanism to further enhance the feature ability and depth of the module to extract the URL. Finally, the softmax function of the fully connected neural network is used to realize the classification and recognition of URL. The experimental results show that the phishing URL recognition model based on the fusion of ON-LSTM and attention mechanism features has better ability to identify phishing URLs, with an accuracy of 98.95% and an F1 value of 98.92%. Compared with the comparison model, this method has better recognition performance.

Citation Download Citation

Qiaojuan Jia, Ming Liu, Xiaoyu Jin, and Dawei Ma "Phishing URL recognition based on ordered neurons long short-term memory neural network and attention mechanism feature fusion", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127181C (1 June 2023); https://doi.org/10.1117/12.2681573

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