Detection and analysis method for image emails

Abstract

The invention relates to a detection and analysis method for image emails. The method is used for detection and analysis on the basis of images in the emails and other content attributes of the emails. The method comprises the steps that firstly, images or subdomain images in the emails are intercepted to be matched with a spam image library of a user, and if matching succeeds, the emails are regarded as spam emails, or a blacklist and a whitelist of the user and a grey list based on the credibility score are searched, and the categories of the emails are obtained; the categories of the emails of which the categories can not be determined are obtained by inquiring a blacklist and a whitelist of friend nodes in the network, wherein the friend nodes are the network nodes having higher email interaction frequency with the current user node; the emails can also be sent to a cloud server for category judgment. The method can effectively detect and filter spam images in the emails, and can carry out multilevel and multi-grade comprehensive detection and analysis on the emails.

Description

technical field [0001] The invention relates to the field of network communication. Specifically, it relates to a method for detecting and analyzing image mails. Background technique [0002] With the development of Internet applications, e-mail has been widely used and has become one of the most basic services on the Internet. Users can exchange information economically, conveniently and quickly with remote users through e-mail. However, while e-mail is gradually becoming an indispensable and important information exchange tool, it is also becoming a commercial advertising method. While receiving useful information, users must also spend a lot of time and energy to classify and identify various emails to filter "junk" emails. However, the existing email classification and identification methods may use a relatively simple classification and identification method This leads to inaccurate results, or the use of overly complex identification methods increases the time cost. ...

AI Technical Summary

Problems solved by technology

The above method can effectively detect and filter spam pictures in emails, and can combine with other detection methods to perform multi-level and comprehensive detection and analysis of emails, which can solve the problem of excessive computational cost and low efficiency in identifying spam emails in the prior art The problem

Images