Automated Email Storm Detection via Context Feature Analysis
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Solution Overview
Problem
Existing email systems require manual intervention to manage and mitigate email storms, which can lead to operational inefficiencies and server overload due to the lack of automated detection and quarantine mechanisms.
Innovation Solution
An information handling system that determines context features from email message payloads to automatically identify and quarantine emails part of a storm, using a processor to set a quarantine indication and store such emails in a designated memory region, thereby preventing server overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual intervention is used to manage email storms, then operational efficiency is maintained through human judgment, but server overload occurs due to lack of automated response and system performance deteriorates
Solution Approach 1:
The system performs preliminary analysis by determining context features from email payloads before full processing occurs. The processor extracts and evaluates context features (such as sender information, recipient lists, attachment types) to identify potential email storms in advance, setting quarantine indications proactively rather than reactively
Solution Approach 2:
The email processing system is segmented into distinct functional modules: context feature determination, quarantine indication setting, and physical quarantine execution. This segmentation allows automated decision-making at each stage, reducing server overload by filtering emails through specialized sub-systems rather than requiring manual intervention for entire email streams
2Reliability
If no automated quarantine mechanism is implemented, then system complexity remains low, but server overload occurs due to unmanaged email storms
Solution Approach 1:
A quarantine mechanism serves as an intermediary between email reception and full system processing. The processor sets quarantine indications based on context feature analysis, and quarantined emails are stored in a designated memory region, preventing them from overwhelming the main email processing system while maintaining overall server performance
Solution Approach 2:
The system performs preliminary analysis by determining context features from email payloads before full processing occurs. The processor extracts and evaluates context features (such as sender information, recipient lists, attachment types) to identify potential email storms in advance, setting quarantine indications proactively rather than reactively
3Productivity
If manual management of email storms is used, then automated processing capacity is preserved, but operational inefficiency occurs due to human intervention requirements
Solution Approach 1:
The email system performs self-service by automatically determining context features, evaluating quarantine indications, and executing quarantine decisions without human intervention. The processor autonomously analyzes email payloads, identifies storm patterns, and manages quarantine operations, eliminating the need for manual email storm management while maintaining high processing throughput
Data Source
AI summary
An information handling system determines context features for an electronic mail message based on a payload of the electronic mail message. A processor adds the context features to the payload of the electronic mail message to create an updated payload. Based on the updated payload, the processor sets a quarantine indication for the electronic mail message to either a first state or a second state. In response to the quarantine indication for the electronic mail message being in the first state, the processor assigns the electronic mail message to an electronic mail storm. In response to the assigning of the electronic mail message being to the electronic mail storm, the processor quarantines the electronic mail message.