Email Content Segmentation for Recipient-Aware Security Screening
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Solution Overview
Problem
Existing email systems lack effective filtering and screening capabilities, particularly in managing sensitive information, leading to inadequate risk assessment and security measures, resulting in potential data exposure and misclassification of emails.
Innovation Solution
A secure computing infrastructure that intercepts electronic messages before transmission, categorizes recipient devices, generates content segments using machine learning, and applies security parameters based on recipient categories to block incompatible messages, utilizing a server or hybrid model for centralized management and resource optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard mail server settings are used for email filtering, then the system is simple to operate, but the filtering precision and risk assessment capability are insufficient
Solution Approach 1:
The patent segments email content into multiple content segments and analyzes each segment separately using machine learning models. This segmentation approach enables precise identification of sensitive information while maintaining manageable system complexity through modular processing.
Solution Approach 2:
The system performs preliminary risk assessment and security parameter selection before email transmission. By categorizing recipient devices and pre-determining security parameters, the system prepares filtering criteria in advance, improving filtering precision without adding operational complexity.
2Reliability
If generic security measures are applied to all emails, then the system is easy to implement, but the security effectiveness for sensitive information is inadequate
Solution Approach 1:
The patent applies different security parameters to different content segments based on their sensitivity and the recipient device category. Instead of uniform security measures, the system tailors security requirements to specific content types and recipient contexts, improving security effectiveness while maintaining reasonable complexity through targeted application.
Solution Approach 2:
The system dynamically selects security parameters based on real-time analysis of email content and recipient device category. Machine learning models adapt security requirements according to the specific message being transmitted, ensuring appropriate security effectiveness without requiring complex manual configuration.
3Measurement precision
If machine learning models are used for security parameter selection, then the risk assessment accuracy is improved, but the computing resource utilization increases
Solution Approach 1:
The system applies machine learning models selectively to content segments that require detailed analysis rather than processing every email uniformly. By focusing computational resources on segments with potential sensitive information or higher risk profiles, the system improves risk assessment accuracy while reducing overall computing resource utilization.
Data Source
AI summary
Secure computing infrastructure for electronic messages is described herein. A system can intercept an electronic message for transmission to a recipient device. The system can determine, prior to transmission of the electronic message for receipt by the recipient device, a category of the recipient device based on a domain name associated with an internet protocol address of the recipient device. The system can generate a plurality of content segments based on overlapping sequences of words in the electronic message. The system can identify, using machine learning models and based on the category of the recipient device, a security parameter to apply to the electronic message. The system can detect, using machine learning models, an incompatibility between a content segment and the security parameter. The system can block, responsive to the detection of the incompatibility, the transmission of the electronic message for receipt by the recipient device.