Interval forecasting of cyberattack intensity on informatization objects of industry using probability cluster model

Krakovsky, Y. M.; Luzgin, A. N.; Mikhailova, Elena A.

doi:10.1088/1742-6596/1015/3/032088

Cited by 1 publication

(1 citation statement)

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“…Cova, Chen, Chang, et al detected and analyzed "drive-by-download" on the web as a representative means of spreading malicious code [13,14,15,16]. In addition, Han found that the large-scale cyber terror attack in Korea and the cyber-attack against Sony Pictures were committed by the same attacker group through case-based reasoning [17,28,29]. Many activities are also conducted to share cyber-attack information in the standard aspect.…”

Section: Related Workmentioning

confidence: 99%

Cyber-attack group analysis method based on association of cyber-attack information

Son¹,

Kim²,

Lee³

2020

KSII TIIS

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Cyber-attacks emerge in a more intelligent way, and various security technologies are applied to respond to such attacks. Still, more and more people agree that individual response to each intelligent infringement attack has a fundamental limit. Accordingly, the cyber threat intelligence analysis technology is drawing attention in analyzing the attacker group, interpreting the attack trend, and obtaining decision making information by collecting a large quantity of cyber-attack information and performing relation analysis. In this study, we proposed relation analysis factors and developed a system for establishing cyber threat intelligence, based on malicious code as a key means of cyber-attacks. As a result of collecting more than 36 million kinds of infringement information and conducting relation analysis, various implications that cannot be obtained by simple searches were derived. We expect actionable intelligence to be established in the true sense of the word if relation analysis logic is developed later.

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