A distributed intelligent mail analysis and filtering method, system and storage medium

Abstract

The invention provides a distributed intelligent mail analysis and filtering method, system and storage medium. The present invention distributes mails to multiple computing servers for concurrent processing, extracts mail elements, and performs text extraction and OCR character recognition on files such as documents, pictures, and compressed packages in attachments, and then automatically performs data processing on the extracted information Mining and classification, and finally stored in ElasticSearch according to certain rules. In ElasticSearch, mass emails can be quickly and flexibly filtered, intelligently counted, visualized correlation analysis and full-text search can be intuitively and quickly found. Manual browsing time is long and the efficiency is low.

Description

Technical field [0001] The present invention relates to the field of mail data processing, in particular, a distributed intelligent mail analysis filtering method, system, and storage medium. Background technique [0002] The email is a common communication communication method on the LAN and the Internet. It is an indispensable way to communicate with most companies, especially those involving import and export trade. The mail carries a variety of effective information including contacts, subject content, transmission and receiving time, accessory data, and geographic location. It is very valuable data for forensic analysts. [0003] At present, the analysts have two basic ways to analyze. Word search. The second is to analyze all mail by single-machine forensics software, view all messages in a list in the forensic software. [0004] But for the current hundred GB, the number of pieces of mail, the traditional analytical method and tool efficiency are low, and the relationship ...

AI Technical Summary

Problems solved by technology

[0004] However, for the currently hundreds of gigabytes and millions of emails involved in the case, the traditional analysis methods and tools are inefficient. It is no longer applicable to the scenarios of massive email analysis such as customs inspection and smuggling, internal enterprise investigation, etc.

[0005] It can be seen that the main defects of the existing technology are: first, the software is a stand-alone version, the analysis speed is limited by the performance of a single machine, and it cannot be analyzed collaboratively, and cannot cope with the rapid processing of increasingly large and massive mail data

Second, the analysis results are usually stored in traditional relational databases. When the amount of data increases, the speed of search and filtering will decrease significantly, reducing the efficiency of analysis.

The third is that the processing of the email content is limited to the email text, and the documents, pictures, compressed files and other data in the attachment cannot be effectively retrieved, and no further data mining has been done on the text and attachments, and a lot of manual reading work is still required to discover them. clues

Fourth, the relationship between email addresses and emails is mostly sorted out manually and cannot be displayed

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