EARLY CYBER THREATS DETECTION MODEL BASED ON INTELLECTUAL INTEGRATION OF IOC, LOG AND DARK WEB MONITORING DATA IN CYBER INTELLIGENCE PRACTICE

Authors

  • Dostonbek Tojimatov a:1:{s:5:"ru_RU";s:20:"TATU Farg'on filiali";}

Keywords:

cyber threat, IoC (Indicators of Compromise), log monitoring, Dark Web analysis, Machine learning, Real-time, model.

Abstract

In today’s era, as the complexity and scope of cyber threats continue to grow, traditional methods of threat detection through cyber intelligence operations often fail to ensure the effectiveness of real-time operations. This study proposes an intelligent threat detection model based on the integration of IoC metrics, log file monitoring, and Dark Web analysis data to improve cyber intelligence operations. The model includes three main stages, namely 1) data integration, 2) threat analysis and real-time visualization, and 3) automatic alerting.

References

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Tojimatov, D. (2023, October). KIBERRAZVEDKA OLIB BORISH STRATEGIYASI BOSQICHLARI. In Conference on Digital Innovation:" Modern Problems and Solutions".

Tojimatov, D. X. (2023). KIBERTAHDIDLARNI OLDINI OLISHDA KIBERRAZVEDKA AMALIYOTI VA UNING USTUVOR VAZIFALARI. Al-Farg’oniy avlodlari, 1(4), 82-85.

Published

2024-12-26

How to Cite

Tojimatov, D. (2024). EARLY CYBER THREATS DETECTION MODEL BASED ON INTELLECTUAL INTEGRATION OF IOC, LOG AND DARK WEB MONITORING DATA IN CYBER INTELLIGENCE PRACTICE. The Descendants of Al-Fargani, (4), 163–167. Retrieved from http://al-fargoniy.uz/index.php/journal/article/view/693

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