Recent Progress of Using Knowledge Graph for Cybersecurity

Author:

Liu KaiORCID,Wang Fei,Ding Zhaoyun,Liang Sheng,Yu Zhengfei,Zhou YunORCID

Abstract

In today’s dynamic complex cyber environments, Cyber Threat Intelligence (CTI) and the risk of cyberattacks are both increasing. This means that organizations need to have a strong understanding of both their internal CTI and their external CTI. The potential for cybersecurity knowledge graphs is evident in their ability to aggregate and represent knowledge about cyber threats, as well as their ability to manage and reason with that knowledge. While most existing research has focused on how to create a full knowledge graph, how to utilize the knowledge graph to tackle real-world industrial difficulties in cyberattack and defense situations is still unclear. In this article, we give a quick overview of the cybersecurity knowledge graph’s core concepts, schema, and building methodologies. We also give a relevant dataset review and open-source frameworks on the information extraction and knowledge creation job to aid future studies on cybersecurity knowledge graphs. We perform a comparative assessment of the many works that expound on the recent advances in the application scenarios of cybersecurity knowledge graph in the majority of this paper. In addition, a new comprehensive classification system is developed to define the linked works from 9 core categories and 18 subcategories. Finally, based on the analyses of existing research issues, we have a detailed overview of various possible research directions.

Funder

The Science and Technology Innovation Program of 953 Hunan Province

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference137 articles.

1. Colonial Pipeline Paid Close to $5 Million in Ransomware Blackmail Paymenthttps://www.calvin.edu/library/knightcite/index.php

2. Lack of Experts in Cyber Securityhttps://www.threatq.com/lack-of-experts-in-cyber-security/

3. Applications of Machine Learning Techniques in the Realm of Cybersecurity

4. Cyber conflict short of war: a European strategic vacuum

5. Advanced Persistent Threat: Understanding the Danger and How to Protect Your Organization;Cole,2012

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