Spam Filtering via User Confidence and Message Signatures

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Solution Overview

Problem

Current spam filtering systems are inefficient in recognizing spam campaigns early and incorporating user feedback, leading to increased costs and response times, and they struggle with maintaining a reliable user set due to the lack of consensus on spam definitions and inadequate near-duplicate message detection.

Innovation Solution

A computer-implemented method and system that receives user reports, calculates confidence values for users, and filters messages based on predetermined thresholds to identify and filter spam campaigns by associating confidence values with message signatures, using techniques like the I-Match algorithm for clustering similar messages and adjusting confidence values based on user feedback.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If conventional spam filtering systems are used, then spam detection can be performed, but response time is slow and costs increase due to inability to quickly recognize spam campaigns

Engineering Contradiction:

Improvespam filtering response timeVSAvoidspam campaign detection accuracy

Core Design Contradiction:

Loss of timeVSReliability

Solution Approach 1:

The system performs preliminary actions by pre-calculating signature values for message clusters and maintaining a database of known spam signatures before new messages arrive. When messages are received, the system quickly compares them against pre-computed signatures rather than analyzing each message from scratch, enabling rapid identification of spam campaigns while maintaining high detection accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adapts by continuously updating confidence values for users and re-calculating signature values as new spam patterns emerge. The confidence values are dynamically adjusted based on user feedback and system learning, allowing the filtering mechanism to evolve rapidly in response to new spam campaigns while maintaining reliability

Inventive Principle:

Principle #15Dynamics

2Reliability

If user feedback is incorporated into spam filtering, then detection accuracy improves, but system complexity increases due to need to manage user confidence values and feedback processing

Engineering Contradiction:

Improvespam detection reliabilityVSAvoiduser feedback processing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system implements a structured feedback mechanism where user reports are systematically processed to update confidence values. User feedback directly influences the confidence scores assigned to reporters, which in turn affect the weight given to their future reports. This closed-loop feedback system improves detection reliability while managing complexity through automated confidence value adjustments rather than manual configuration

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system manages complexity by changing parameters dynamically - specifically, confidence values are automatically adjusted based on feedback patterns rather than requiring manual intervention. The confidence parameter evolves over time based on user behavior and report accuracy, allowing the system to adapt to changing spam patterns without increasing operational complexity

Inventive Principle:

Principle #35Parameter changes

3Productivity

If signature-based deduplication is used to identify spam campaigns, then spam recognition speed improves, but false positives increase due to near-duplicate detection challenges

Engineering Contradiction:

Improvespam filtering efficiencyVSAvoidfalse positive rate

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system applies partial action by calculating signature values based on selected message features rather than analyzing entire messages. By focusing on key distinguishing features and cluster characteristics rather than complete message content, the system achieves rapid spam identification while reducing false positives from over-matching similar but legitimate messages

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS9485269B2Systems and methods for reporter-based filtering of electronic communications and messages

Publication Date: 2016.11.01 YAHOO ASSETS LLC

AI summary

Methods and apparatuses for filtering electronic communications in a communication system. The method includes receiving a message report from a user in response to an electronic message received by the user, and identifying a confidence value associated with the user from whom the message report is received. The method also includes adding, if the confidence value exceeds a predetermined confidence value threshold, the confidence value to a signature value associated with the electronic message, and determining if the signature value exceeds a signature value threshold. The method further includes filtering the electronic message if the signature value exceeds the signature value threshold.