Illegal website identification system and method based on critical path

Abstract

The invention relates to an illegal website identification system and method based on a critical path. A system framework is divided into four layers, namely a user layer, an application service layer, a technical support layer and a data storage layer. The user layer provides a main account of the system; the application service layer provides a main function module of the system; the technical support layer comprises a relevant tool used in the system development process and a core algorithm program; the data storage layer provides data used in the system. According to the detailed functional division, the function module of the illegal website identification system based on the critical path comprises data preprocessing, website similarity calculation, website clustering, illegal website critical path extraction and illegal website identification. The system develops a similarity calculation program based on the Path through taking URL self characteristics as research start points, can accurately calculate the similarity among websites and obtain the effective URL critical path based on the website similarity and a Fast Unfolding clustering algorithm, and finally can discover illegal websites in unknown websites through the URL critical path.

Description

technical field [0001] The present invention relates to the field of website identification and classification, in particular to the technical field of illegal website identification, and specifically refers to an illegal website identification system and method based on a critical path. Background technique [0002] Identifying illegal websites is an important task in the field of network security, and the accuracy and timeliness of the identification method have higher requirements. At present, the existing website clustering research mostly starts from the perspective of user access behavior, and obtains the data of user access to the website from the Web log, including the user's access path, access frequency, access time, and access hobbies, etc., and establishes a user transaction matrix. Then cluster user groups and websites. However, this indirect website clustering method is not accurate enough to achieve fast identification of illegal websites. In the professiona...

AI Technical Summary

Problems solved by technology

However, this indirect website clustering method is not accurate enough to achieve fast identification of illegal websites

In the professional field of automatic identification of illegal websites, existing researches are mainly based on three types of technologies: blacklist, static detection and dynamic detection. However, the workload and cost of establishing and maintaining blacklists are large, and static detection mostly obtains website static data through web crawlers. , the detection of unknown illegal websites is not timely enough, the implementation of dynamic detection is difficult, and it is mainly aimed at websites linked to horses, and the types of websites that can be identified are limited

To sum up, it can be seen that there are not many researches on identifying illegal websites through website similarity and website key path, especially the research on the key path of URL of illegal websites is still very little.

Images