Phishing website identification based on Bi-LSTM with attention mechanism
With the popularization of the Internet,phishing websites that people contact are one of the most common types of cybercrime,causing huge economic loss and information leakage.Based on this,a model based on Bi-LSTM(bidirectional long short memory neural network)combined with an attention mechanism is proposed to recognize phishing websites.Data were prepro-cessed,word vectors were constructed using the Word2Vec model,features is extracted using Bi-LSTM,attention weights were cal-culated using the attention mechanism to generate final feature vectors,and the classification of phishing websites was obtained by using the sigmoid function.Experimental results show that the model is 98.3%effective in detecting phishing sites,and can effec-tively deal with the threat of phishing attacks and maintain the security of phishing sites.
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