大数据驱动的威胁情报分析与预警模型构建

Peng Zhang
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引用次数: 0

摘要

随着大数据技术的发展,其在各个领域的应用越来越广泛,特别是在威胁情报分析和预警领域。利用大数据的处理能力和数据挖掘技术,可以从海量、多面数据中发现威胁的模式和规律,实现有效的威胁预警。然而,大数据驱动的威胁情报分析与预警模型构建是一个具有挑战性的过程,涉及到对大数据的理解与处理、威胁情报分析的方法与工具、预警模型的设计与实现、预警模型的验证与评估等多个方面。本文旨在全面描述这一过程,为大数据驱动的威胁情报分析与预警提供指导和参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data-Driven Threat Intelligence Analysis and Early Warning Model Construction
With the development of big data technology, its application in various fields is becoming increasingly widespread, especially in the field of threat intelligence analysis and early warning. By using the processing power of big data and data mining technology, patterns and laws of threats can be discovered from the massive and multifaceted data, thus realizing effective early warning of threats. However, big data-driven threat intelligence analysis and early warning model construction is a challenging process, which involves various aspects such as understanding and processing of big data, methods, and tools for threat intelligence analysis, design and implementation of early warning models, and validation and evaluation of early warning models. This paper aims to comprehensively describe this process to provide guidance and reference for big data-driven threat intelligence analysis and early warning.
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