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THREAT DETECTION PLATFORMS FOR DETECTING, CHARACTERIZING, AND REMEDIATING EMAIL-BASED THREATS IN REAL TIME

机译:实时检测,表征和补救基于电子邮件的威胁的威胁检测平台

摘要

Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.
机译:传统的电子邮件过滤服务不适合识别复杂的恶意电子邮件,因此可能允许复杂的恶意电子邮件错误地到达收件箱。此处介绍的威胁检测平台旨在采用一种集成方法来检测安全威胁。例如,威胁检测平台在接收到表示个人同意访问企业员工过去收到的电子邮件的输入后,可以下载过去的电子邮件以构建机器学习(ML)模型,该模型可以理解与内部联系人进行交流的规范(例如其他员工)和/或外部联系人(例如供应商)。通过将ML模型应用于传入电子邮件,威胁检测平台可以有针对性地实时识别安全威胁。

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