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Detecting of targeted malicious email

机译:检测目标恶意电子邮件

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摘要

Network providers are the one which allows all type of emails for communication purpose. While transferring the messages some malicious emails are received by the users this causes many problems either at the server side or at the user side. This type of emails may contain unsolicited content, or it could be due to the message being crafted. Persistent threat features, such as threat actor locale and unsolicited email crafting tools, along with recipient oriented features. Current detection techniques work well for spam and phishing because its easy to detect mass-generated email sent to millions of addresses. TME mainly targets single users or small groups in low volumes. TME can pretend network exploitation. Hence for detection of TME is vital work. This paper explains how the malicious emails are classified. In order to classify here we are using `Random Forest Classifier'. This classifier focuses on feature extraction.
机译:网络提供商是允许所有类型的电子邮件用于通信目的的提供商。在传输消息时,用户会收到一些恶意电子邮件,这会在服务器端或用户端引起许多问题。这种类型的电子邮件可能包含不请自来的内容,或者可能是由于邮件是经过精心设计的。持久的威胁功能,例如威胁参与者的语言环境和未经请求的电子邮件制作工具,以及面向收件人的功能。当前的检测技术非常适合垃圾邮件和网络钓鱼,因为它很容易检测发送到数百万个地址的大量生成的电子邮件。 TME主要针对小批量的单个用户或小组。 TME可以假装网络利用。因此,对于TME的检测至关重要。本文介绍了恶意电子邮件的分类方式。为了在这里进行分类,我们使用了“随机森林分类器”。该分类器专注于特征提取。

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