Open AccessCMS System Identification Based on Improved Algorithm of Apriori
Author(s) -
Zhonglin Liu,
Yan Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1631/1/012062
Subject(s) - apriori algorithm , computer science , relevance (law) , identification (biology) , data mining , a priori and a posteriori , the internet , feature (linguistics) , information retrieval , association rule learning , world wide web , philosophy , linguistics , botany , epistemology , biology , political science , law
Web applications on the Internet are often attacked by various vulnerabilities. Once various vulnerabilities are published, it becomes more and more important to quickly and accurately locate the affected Web application or system from the list of website resources. In this paper, based on the data and information of similar CMS websites, the improved Apriori algorithm is used to extract the features of CMS websites and their association rules, which can be used to quickly identify whether unknown websites are CMS templates of this type. Through experimental tests, four feature information used to identify WordPress is obtained. According to these features and relevance, the system type website can be identified more accurately.