Spam Filter Rule Prioritization via Dynamic Subset Selection
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Solution Overview
Problem
Existing email filtering systems face inefficiencies as the number of spam filtering rules grows, leading to increased processing time and resource usage, as not all rules are applicable to every message, making it inefficient to evaluate every rule against a message.
Innovation Solution
The system selects and prioritizes spam filtering rules based on email characteristics, global filtering rule statistics, and recipient profiles, applying the most relevant and efficient rules first to determine if a message is spam, thereby reducing processing time and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If every filtering rule is evaluated against every email message, then spam detection thoroughness is improved, but processing time and resource usage increase
Solution Approach 1:
The patent segments the complete set of filtering rules into multiple subsets based on different criteria (rule characteristics, email characteristics, performance metrics). Each subset contains rules that are most relevant for specific types of emails or spam patterns. This segmentation allows the system to evaluate only the appropriate subset against each email message rather than all rules, thereby maintaining thorough spam detection while reducing processing time and resource consumption.
2Measurement precision
If every filtering rule is evaluated against every email message, then spam detection accuracy is improved, but processing resources increase
Solution Approach 1:
The patent applies partial action by evaluating only a selected subset of filtering rules against each email message rather than the complete set. The subset is determined based on email characteristics, rule characteristics, and performance statistics. This partial evaluation maintains sufficient spam detection accuracy by focusing on the most relevant rules while significantly reducing the processing resources required compared to evaluating all rules.
3Reliability
If a large number of filtering rules are maintained to identify spam, then spam detection capability is improved, but processing efficiency deteriorates
Solution Approach 1:
The patent implements dynamic rule subset selection where the set of filtering rules evaluated against each email message is not fixed but dynamically determined based on email characteristics, rule characteristics, and performance statistics. This dynamic approach allows the system to maintain a large number of filtering rules for comprehensive spam detection capability while achieving high processing efficiency by selectively applying only the most relevant rules to each message.
Solution Approach 2:
The patent changes the parameter of rule application from a static all-or-nothing approach to a dynamic selective approach. By varying the subset of rules applied based on email characteristics, rule effectiveness metrics, and performance statistics, the system maintains comprehensive spam detection capability while optimizing processing efficiency for different message types and spam patterns.
Data Source
AI summary
Techniques to select and prioritize the application of spam filtering rules in a way that reduces processing time may include receiving an email message for a recipient at a spam filter and extracting email characteristics from the message. Global filtering rule statistics and a profile for the recipient may be retrieved. The technique may include selecting a subset of rules from a set of filtering rules according to the email characteristics, the global filtering rule statistics, and/or the recipient characteristics. The subset of rules may be prioritized and applied to the message from highest priority to lowest until a determination of whether the message is spam is reached. Other embodiments are described and claimed.