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首页> 外文期刊>International journal of digital crime and forensics >Models for the Detection of Malicious Intent People in Society
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Models for the Detection of Malicious Intent People in Society

机译：社会上恶意意图分子的检测模型

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This article describes how in less than two decades, internet in mobile phones has grown from a curiosity to an essential element of modern life. Although, this mind-boggling growth has no doubt facilitated international commerce, trade, and travel, it is also being used in the planning and coordination of criminal activities. These types of attacks are often referred to as socio-technical attacks. These attacks are targeted at these sensitive points to society or national security and may have a devastating impact. Often, organized, sponsored, and trained groups are involved to disguise the intelligence system, deployed for the detection of such attacks. Prior detection of such attacks may reduce its impact. In this article, the authors have developed an efficient model to detect malicious node in huge and complex corpus of data associated with call detail record (CDR). This model analyses CDRs to identify covert nodes operating within society for malicious intent.
机译：本文介绍了在不到二十年的时间里，移动电话中的互联网如何从好奇心发展为现代生活的基本要素。尽管这一令人难以置信的增长无疑促进了国际贸易，贸易和旅行的发展，但也被用于计划和协调犯罪活动。这些类型的攻击通常称为社会技术攻击。这些攻击针对的是社会或国家安全的敏感点，可能会造成破坏性影响。通常，由组织，赞助和训练有素的小组参与掩盖部署用于检测此类攻击的情报系统。事先检测到此类攻击可能会降低其影响。在本文中，作者开发了一种有效的模型，可以检测与呼叫详细记录（CDR）相关的庞大而复杂的数据集中的恶意节点。该模型分析CDR，以识别出于恶意目的在社会中运作的秘密节点。

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