Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues for Human Participatory Based on Association Rules

Frontiers in Psychology

Lin Zhang¹  Xuyu Li²  Runhua Tang³  Zhi Li⁴ 

[1] Faculty of Humanities and Arts, Macau University of Science and Technology, Taipa, Macau;School of Computer and Data Engineering, NingboTech University, Ningbo, China;School of Journalism and Communication, Dalian University of Foreign Languages, Dalian, China;School of Media and Law, NingboTech University, Ningbo, China;College of Media and International Culture, Zhejiang University, Hangzhou, China;

关键词: association rules;    data mining;    network sovereignty;    cyberspace security;    Apriori algorithm;   

DOI  :  10.3389/fpsyg.2020.582480

来源: Frontiers

【 摘 要 】

This study explored the global cyberspace security issues, with the purpose of breaking the stereotype of people’s cognition of cyberspace problems, which reflects the relationship between interdependence and association. Based on the Apriori algorithm in association rules, a total of 181 strong rules were mined from 40 target websites and 56,096 web pages were associated with global cyberspace security. Moreover, this study analyzed support, confidence, promotion, leverage, and reliability to achieve comprehensive coverage of data. A total of 15,661 sites mentioned cyberspace security-related words from the total sample of 22,493 professional websites, accounting for 69.6%, while only 735 sites mentioned cyberspace security-related words from the total sample of 33,603 non-professional sites, accounting for 2%. Due to restrictions of language, the number of samples of target professional websites and non-target websites is limited. Meanwhile, the number of selections of strong rules is not satisfactory. Nowadays, the cores of global cyberspace security issues include internet sovereignty, cyberspace security, cyber attack, cyber crime, data leakage, and data protection.

【 授权许可】

CC BY