An Empirical Study of Intelligent Security Analysis Methods Utilizing Big Data
Yang-Ha Chun, Moon-ki Cho
Abstract
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.