<?xml version="1.0" encoding="UTF-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <front>
        <journal-meta>
            <journal-title-group>
                <journal-title>Journal of Global Humanities and Social Sciences</journal-title>
            </journal-title-group>
            <issn media_type="print">2737-5374</issn>
            <issn media_type="electronic">2737-5382</issn>
            <publisher>
                <publisher-name>BONI FUTURE DIGITAL PUBLISHING CO.,LIMITED </publisher-name>
            </publisher>
            <url>https://ojs.bonfuturepress.com/index.php/GHSS/article/view/1416</url>
            <volume>4</volume>
            <issue>04</issue>
            <year>2023</year>
            <published-time>2023-08-29</published-time>
            <title>Big Data-Driven Threat Intelligence Analysis and Early Warning Model Construction</title>
            <author>Peng Zhang</author>
            <abstract>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.</abstract>
            <keywords>big data-driven,threat intelligence,early warning model</keywords>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.61360/BoniGHSS232014160804</article-id>
        </article-meta>
    </front>
    <tbody>
        <back>
            <sec/>
            <ref-list>
                <ref>
                   <element-citation publication-type="journal">
                       <p></p>
                   </element-citation>
                </ref>
            </ref-list>
        </back>
    </tbody>
</article>