Reputation Engine for Spam Detection Using Multi-Level Segmentation
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Solution Overview
Problem
Existing reputation-based systems for identifying undesired messages lack granularity, often incorrectly flagging legitimate messages as spam due to coarse-grained IP address or domain-based filtering, affecting numerous innocent users.
Innovation Solution
A method and system that uses a reputation engine to analyze a tuple of message origin identifiers, including an unfakeable IP address, domain, and user identifiers, to determine the likelihood of a message being undesired, allowing for finer-grained tracking and differentiation between legitimate and spam messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blacklists are used to identify IP addresses that send undesired messages, then the ability to filter spam is improved, but legitimate messages from bonafide users at the same IP address are incorrectly blocked
Solution Approach 1:
The patent segments the reputation assessment by creating multiple hierarchical levels: IP address level, domain level, and message level. This segmentation allows the system to evaluate spam likelihood at different granularities, preventing blanket blocking of all messages from an IP address while still filtering spam effectively.
Solution Approach 2:
The patent applies local quality by assigning different reputation scores to different domains within the same IP address and to different messages from the same sender. Each message is evaluated with its own reputation score based on specific characteristics, allowing legitimate messages to be distinguished from spam even when they share the same origin IP.
2Reliability
If reputation-based techniques using IP address statistics are employed, then spam identification capability is improved, but granularity is insufficient resulting in all messages from an IP address being identified as spam
Solution Approach 1:
The patent divides the reputation tracking system into multiple segments operating at different levels of granularity. The IP address level provides coarse-grained reputation, the domain level provides medium-grained reputation, and the individual message level provides fine-grained reputation. This multi-level segmentation enables precise measurement without sacrificing the ability to detect spam at broader levels.
Solution Approach 2:
The patent adds dimensional complexity by evaluating messages across multiple dimensions simultaneously: IP address reputation, domain reputation, and message-specific characteristics. This multi-dimensional approach transforms the single-dimensional IP address reputation system into a comprehensive multi-factor assessment system that achieves both high reliability and fine measurement precision.
3Device complexity
If coarse-grained IP address or domain-based filtering is used, then spam filtering is simplified, but false positives increase affecting numerous innocent users
Solution Approach 1:
The patent segments the filtering process into distinct hierarchical levels that can be applied in sequence. The system first checks IP address level reputation, then domain level reputation, and finally message level characteristics. This segmented approach maintains relative simplicity while reducing false positives through progressive refinement of the filtering criteria.
Solution Approach 2:
The patent implements preliminary action by pre-calculating and storing reputation scores at multiple levels (IP address, domain, message) before actual message filtering occurs. These pre-computed reputation metrics are readily available when a message arrives, enabling rapid filtering decisions without complex real-time analysis, thus maintaining system simplicity while improving accuracy.
Data Source
AI summary
A system and method for providing a reputation service for use in messaging environments employs a reputation of compiled statistics, representing whether SPAM messages have previously been received from respective a selected set of identifiers for the origin of the message, in a decision making process for newly received messages. In a preferred embodiment, the set of identifiers includes the IP address, a tuple of the domain and IP address and a tuple of the user and IP address and the set of identifiers allows for a relatively fine grained set of reputation metrics to be compiled and used when making a determination of a likelihood as to whether a received message is undesired in accordance with the invention.