A website classification method based on the comprehensive characteristics of darknet websites

Abstract

The invention discloses a website classification method based on the comprehensive characteristics of darknet websites. The method is as follows: 1) Crawl the target darknet website to obtain a marked darknet website training set; 2) extract the information of each website in the collection for word segmentation, construct the word space vector of the website, and calculate each word The weight of the word; the space vector after multiplying the word and the corresponding weight is used as the text feature of the website; 3) extract the label of each website in the training set of the dark net website, construct the space vector of the label of the website, and calculate each The weight of the label; the space vector multiplied by the label and the corresponding weight is used as the structural feature of the website; 4) the text feature and structural feature of each website are combined to obtain the comprehensive feature of the website; 5) the comprehensive features of each website are analyzed training to obtain a classification model; then use the classification model to predict the website to be classified to obtain the category of the website to be classified. The invention improves the website classification efficiency.

Description

technical field [0001] The invention belongs to the field of network data analysis and relates to a website classification method based on the comprehensive characteristics of darknet websites. Background technique [0002] Darknet refers to a private network that uses unconventional protocols and ports and trusted nodes to connect, and data transmission on the darknet is anonymous (Wikipedia). Today's typical darknet technologies include Tor, I2P, Freenet, OneSwam, etc. [0003] The biggest feature of the dark web is the realization of anonymous data transmission for privacy protection. Because of its anonymity, the dark web is often not used to transmit various sensitive information. For example, the dark web contains a lot of information on extremism, drugs, and gun transactions. At the same time, the dark web is also a gathering place for various hacker-related information. In the dark web, there are many hacker forums and hacker markets, where hacker information such ...

AI Technical Summary

Problems solved by technology

[0005] At present, the classification of dark net mostly relies on manual maintenance, which can ensure the accuracy of the classification. However, as the number of dark net websites increases, the cost of manual maintenance will also increase greatly, making it difficult to meet the needs of users for the classification of dark net websites.

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