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Development of a Cyber-Threat Intelligence-Sharing Model from Big Data Sources

机译:利用大数据源开发网络威胁情报共享模型

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As data in cyberspace continues to grow because of the ubiquity of Information Communication Technologies (ICT), it is becoming challenging to obtain context-aware, actionable information from Big Data to timely detect and respond to cyberattacks that are increasing in severity, complexity, and frequency. In fact, cybercriminals are developing and sharing advanced techniques for their cyber espionage, reconnaissance missions, and ultimately devastating attacks. In order to reduce cybersecurity risks and strengthen cyber resilience, strategic cybersecurity information-sharing is a necessity. This article discusses one way of handling large volumes of unstructured data that have been generated by multiple sources across different sectors into a cyber-threat intelligence-sharing model.
机译:随着信息通信技术(ICT)的普及,网络空间中的数据不断增长,从大数据获取情境感知,可操作的信息以及时检测严重性,复杂性和复杂性不断增加的网络攻击并做出响应正变得越来越困难。频率。实际上,网络犯罪分子正在为他们的网络间谍活动,侦察任务以及最终毁灭性攻击开发和共享先进的技术。为了降低网络安全风险并增强网络弹性,必须进行战略性的网络安全信息共享。本文讨论了一种将大量来自不同部门的多个来源生成的非结构化数据处理为网络威胁情报共享模型的方法。

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