Distributed intelligent mail analysis filtering method, system and storage medium

Abstract

The invention provides a distributed intelligent mail analysis filtering method, a system and a storage medium. As that mail is distribute to a plurality of operation servers for concurrent processing, Extract message elements, and to the documents in the attachment, A method for extract text and recognizing OCR character from files such as pictures and compressed packages, data mining and classification are performed automatically on the extracted information, Eventually, it is stored in ElasticSearch according to certain rules, In ElasticSearch, it can quickly filter mass emails, make intelligent statistics, visualize association analysis and full-text retrieval. It can find clues intuitively and quickly, and solve the problems of huge data, long manual browsing time and low efficiency.

Description

technical field [0001] The invention relates to the technical field of mail data processing, in particular to a distributed intelligent mail analysis and filtering method, system and storage medium. Background technique [0002] Email is a common communication method on the local area network and the Internet. It is an indispensable communication method for most enterprises, especially those involved in import and export trade. Emails carry a variety of valid information including contacts, subject content, sending and receiving time, attachment data and geographic location, and are very valuable data for forensic analysts. [0003] At present, there are two basic methods for forensic analysts to analyze. One is to uniformly import emails into a certain email client, use the email client to check the content of each email, and use the search function that comes with the email client to perform key analysis. word search. The second is to parse out all emails through stand-a...

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 It is no longer applicable to the scenarios of massive email analysis such as customs inspection and smuggling, internal enterprise investigation, etc.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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