Email Filtering Risk Assessment and Selective Review
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Solution Overview
Problem
Current e-mail filtering technologies treat all filtered emails uniformly, leading to legitimate emails being incorrectly blocked and lacking user control over potentially useful content, with no safe method for reviewing filtered emails before acceptance or rejection.
Innovation Solution
An apparatus and method that includes a risk assessment module to assign risk values to email sections, a risk management module to block or disclose sections based on user input, and a review interface to selectively reveal blocked content, allowing users to safely review and manage filtered emails.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If e-mail filtering systems block all potentially risky e-mails, then security and work environment safety are improved, but legitimate e-mails are incorrectly filtered and made unavailable to users
Solution Approach 1:
The patent segments the e-mail filtering process into multiple stages: initial filtering to identify potentially risky e-mails, risk assessment to evaluate specific risk factors, and selective blocking where only certain portions or types of e-mails are blocked while others are allowed through or marked for review. This segmentation allows the system to maintain high security while preserving access to legitimate e-mails.
Solution Approach 2:
The system changes the parameter of filtering from a binary block/allow decision to a multi-level risk assessment with adjustable risk thresholds. By modifying risk thresholds dynamically, the system can adapt its filtering strictness to balance security requirements against the need to deliver legitimate e-mails, reducing false positives.
2Device complexity
If e-mail filtering systems treat all filtered e-mails uniformly, then filtering simplicity is maintained, but users cannot selectively review potentially useful e-mails
Solution Approach 1:
The patent introduces dynamic user control mechanisms that allow users to adjust their e-mail review preferences and risk tolerance levels. The system dynamically adapts to user behavior by learning from review patterns and automatically adjusting filtering parameters, providing both simplicity and user control.
Solution Approach 2:
The system implements feedback loops where user actions (reviewing, blocking, or accepting e-mails) are captured and used to refine future filtering decisions. This feedback mechanism allows users to influence the filtering behavior over time, improving ease of operation while maintaining systematic filtering.
3Productivity
If e-mail filtering systems block e-mails on a pass-fail basis only, then filtering speed is maintained, but users have no control over potentially useful e-mails
Solution Approach 1:
Instead of applying full blocking action to all potentially risky e-mails, the system applies partial action by selectively blocking only the most suspicious e-mails while allowing others to pass through to user review. This partial action approach maintains filtering speed for clear cases while providing user control for borderline cases.
Solution Approach 2:
The patent introduces an intermediary review stage between filtering and final delivery. E-mails that are neither clearly safe nor clearly malicious are placed in a review queue where users can exercise control. This intermediary mechanism preserves filtering speed for decisive cases while enabling user control for ambiguous cases.
4Reliability
If users access junk e-mail locations to find filtered e-mails, then filtering effectiveness is maintained, but users must sort through thousands of offensive and risky e-mails
Solution Approach 1:
The system performs preliminary risk assessment and categorization before e-mails reach the user's junk folder. By pre-evaluating and tagging e-mails with risk levels and categories during the filtering process, the system prepares the groundwork for efficient user review, reducing the time needed to locate legitimate e-mails.
Solution Approach 2:
The patent employs visual indicators (analogous to color changes) to highlight the risk level and type of filtered e-mails. Different risk levels are indicated through visual cues in the user interface, allowing users to quickly identify and prioritize review of potentially legitimate e-mails versus clearly malicious ones, significantly reducing search time.
Data Source
AI summary
An apparatus and method are disclosed for selectively filtering and inspecting incoming e-mail. The steps to selectively filter and inspect incoming e-mail include: assigning a risk value to each section of an incoming e-mail, presenting the incoming e-mail with sections blocked based on the risk value, and selectively disclosing blocked sections of the e-mail to a reviewer based on input from the reviewer. The method provides a way for a reviewer to filter risky e-mails based on multiple criteria, and safely review filtered e-mails to ensure legitimate e-mails are not incorrectly filtered.