Malicious text detection method and device, electronic equipment and storage medium
A detection method and technology of electronic equipment, applied in the computer field, can solve the problems of low accuracy of the detection method and achieve the effect of improving the accuracy
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Embodiment 1
[0064] Figure 1a is a flow chart of a malicious text detection method shown according to an exemplary embodiment, such as Figure 1a As shown, this method can improve the accuracy of malicious text detection.
[0065] The subject of execution of the method includes but is not limited to servers, personal computers, notebook computers, tablet computers, smart phones and other intelligent electronic devices that can execute predetermined processing procedures such as logic calculations by running predetermined programs or instructions. Wherein, the server may be a single server or multiple server groups.
[0066] Optionally, the server may further include at least one database for storing text recognition models, malicious text data, malicious users, and so on. When the servers are a server group, identified malicious text data, malicious websites, malicious users, etc. can be shared among each server in the server group. The method for malicious text detection may include the...
Embodiment 2
[0125] In step S1022, when calculating the first similarity between the normalized text to be detected and each malicious text, and calculating the second similarity between the converted text and each malicious text, the calculation can be performed according to the text vector of the text, The text vector of the text can be generated by the pre-trained model.
[0126] Combine the following figure 2 A method for generating a text vector is introduced. It should be noted that the method for generating a text vector is only an exemplary description, and does not impose any limitation on the method provided by the embodiments of the present disclosure.
[0127] Optionally, considering the process of building a text classification model based on the neural network of the encoder-decoder framework, the input source sentence can obtain a word vector with a fixed dimension and complete semantic features through the encoder of the neural network. Features, the present disclosure ca...
Embodiment 3
[0143] image 3 It is a block diagram of an apparatus for detecting malicious text according to an exemplary embodiment. refer to image 3 , the device 300 includes a word vector determination module 301 , a similarity determination module 302 , and a malicious text determination module 303 .
[0144] The normalization processing module 301 is configured to perform normalization processing on the text to be detected to obtain the normalized text to be detected;
[0145] The similarity determining module 302 is configured to determine the highest similarity between the malicious text in the malicious text library and the text to be detected based on at least the normalized text to be detected, wherein the highest similarity is at least the normalized The highest similarity among the similarities between the text to be detected and each malicious text in the malicious text library;
[0146]The malicious text determining module 303 is configured to determine that the text to b...
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