Email security analysis

Abstract

The technology described herein visibly depicts hidden message traits to help users determine whether an email is genuine or deceptive. The hidden message traits are revealed by identifying and changing attributes that keep the hidden traits from being displayed in a rendered message. Spam messages, phishing messages, and messages that include or link to malicious programs (e.g., malware, ransomware) are examples of unwanted messages that can harm a recipient. These messages often rely on deception to get past email filtering systems and to trick a user into acting on content in a message. The deception often involves including hidden traits in a message that fool an automated filtering system. The technology described herein shows the visible traits to a user by including them in the rendered version of the message.

Description

Background technique [0001] E-mail is a widely used communication tool that provides a fast and inexpensive way of communicating between individuals and groups. Spam emails, phishing emails, and emails that include or link to malicious programs (eg, malware, ransomware) pose an increasing risk to users, companies, and computing devices. Efforts have been made by users to use filtering systems to identify harmful and / or malicious email before it is received. Filtering systems may use natural language processing or other mechanisms to categorize emails. Currently, no email filtering system is perfect. Some benign emails are misclassified as spam, while others reach user inboxes. When an email is classified as benign, there is a small chance that the email is actually malicious. When an email is classified as malicious, there is a small chance that the email is actually benign. In a corporate environment, some emails are quarantined instead of being delivered to the trash fo...

AI Technical Summary

Problems solved by technology

However, this is often a manual assessment, which is time-consuming and error-prone

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