Research on Web Components Association Relationship Based on Data Mining
Kaiming Yang, Tianyang Zhou, Junyi Wang, Junhu Zhu · 2022 2nd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) · 2022
The security of web components is increasingly concerned by the industry, and identifying web components is of great significance to both network attack and defense. To solve this problem, first, a positive and negative association rule mining method based on the DW-SCCI framework is proposed. The DW-SCCI framework performs weighted frequent itemsets mining based on dynamic item weights, and then performs positive and negative association rule mining based on indicators such as interest. Second, an association rule quality evaluation method based on the weight of the common rule index is proposed, which is used to evaluate the quality of association rules mined by different algorithms. Third, on the basis of mining association rules, the application scenarios of association rules are analyzed and studied. The experimental results show that the positive and negative association rules mined by the DW-SCCI framework are of high quality, and have good results in Web component identification and abnormal website mining.