Visualizing Interesting Patterns in Cyber Threat Intelligence Using Machine Learning Techniques

被引:6
作者
Ejaz, Sarwat [1 ]
Noor, Umara [1 ]
Rashid, Zahid [2 ]
机构
[1] Int Islamic Univ, Dept Comp Sci & Software Engn, Islamabad, Pakistan
[2] Seoul Natl Univ, Coll Engn, Technol Management Econ & Policy Program, 1 Gwanak Ro, Seoul 08826, South Korea
关键词
Cyber threat intelligence; machine learning; visual analytics; tactics techniques and procedures; cyber threat actor; malware;
D O I
10.2478/cait-2022-0019
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In an advanced and dynamic cyber threat environment, organizations need to yield more proactive methods to handle their cyber defenses. Cyber threat data known as Cyber Threat Intelligence (CTI) of previous incidents plays an important role by helping security analysts understand recent cyber threats and their mitigations. The mass of CTI is exponentially increasing, most of the content is textual which makes it difficult to analyze. The current CTI visualization tools do not provide effective visualizations. To address this issue, an exploratory data analysis of CTI reports is performed to dig-out and visualize interesting patterns of cyber threats which help security analysts to proactively mitigate vulnerabilities and timely predict cyber threats in their networks.
引用
收藏
页码:96 / 113
页数:18
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