文章基本信息

标题：An Empirical Study of Intelligent Security Analysis Methods Utilizing Big Data
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作者：Yang-ha Chun ; Moon-ki Cho
期刊名称：Webology
印刷版ISSN：1735-188X
出版年度：2022
卷号：19
期号：1
页码：4672-4681
DOI：10.14704/WEB/V19I1/WEB19311
语种：English
出版社：University of Tehran
摘要：The frequency of cyber-terrorist attacks targeting broadcasting companies or key financial institutions, in which PCs affected by malicious code obstruct normal operations, has been increasing. With the widespread availability of internet technology, the frequency of intelligent cyber-attacks in virtual cyber environments, such as APT attacks, continues to rise. Through an intelligent analysis of cyber threats which are still unknown, it is possible to prevent security accidents before they occur through the use of intelligent security analysis methods based on big data. The researcher conducted this empirical study concerning intelligent security analysis methods utilizing big data which are capable of preventing cyber threats, while protecting information assets from risks through evaluation and prediction.
关键词：Behavior-Based;Signature;APT;Big Data Analytics;ISO27001