A design of IL-CyTIS for automated cyber threat detection

As cyber squabbling has been intensified, the necessity of sharing cyber threat information has increased Therefore, attempts to develop a technology to upgrade and deepen the related system will continue. In particular, it is anticipated that automated response and analysis using machine learning will be actively conducted In this paper, we design and propose IL-CyTIS (a unified and lightened information structure) by customizing STIX (a cyber threat information expression standard) for the input and analysis vi'a machine learning before conducting a study using machine learning to derive new information from existing cyber threat information. Then, we discuss its actual application in machine learning.

I. Introduction

In today's cyberspace, attackers have developed new and persistent attacks, and various attacks are consistently occurring. Attackers often use existing attack methods or their unique methods, but they sometimes create communities to share information for more efficient and complex attacks. They share the “zero-day” vulnerability to a specific target or new attack techniques through the communities. Therefore, similar attacks may be performed by several attackers.