A malicious URL detection system and method based on automatic feature extraction
A feature extraction and detection system technology, applied in transmission systems, special data processing applications, instruments, etc., can solve problems such as the lack of popular URL detection software, improve the scope of application and accuracy, avoid manual errors, and improve adaptability Effect
Active Publication Date: 2018-12-14
SHANGHAI JIAO TONG UNIV
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The invention discloses a malicious URL detection system and a malicious URL detection method based on automatic feature extraction, which relates to the malicious URL detection field. The malicious URL detection system comprises a preprocessing module, a parallel learning module and a detection classification module. The preprocessing module takes the URL of the web page as an input, and convertsthe URL structural features, the web page text content and structural features, and the image features extracted by the preprocessing into three digital matrices containing feature vectors respectively. The parallel learning module uses three independent depth learning networks of different algorithms to process the three digital matrices to obtain three probability matrices. The detection and classification module inputs the three probability matrices to a fully connected network for further processing to give a final classification result. The invention combines the depth learning model ofthe text and the image with the malicious URL detection, comprehensively extracts various information of the web page, and improves the application scope and accuracy of the detection method.
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