Centralized Spam Center for Network Message Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current spam reporting standards in communication networks are insufficient, failing to adequately protect the network from spam messages due to lack of effective detection and filtering mechanisms.
Innovation Solution
A centralized spam center collects and analyzes spam reports from various entities within the network to generate and distribute spam filtering rules, enabling entities to filter out spam messages effectively by updating and disseminating these rules across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized spam agent is implemented to track and report spam messages, then spam detection capability is improved, but the system complexity and infrastructure requirements increase
Solution Approach 1:
The patent combines multiple spam detection entities (message centers, service centers, end user devices) into a unified centralized spam agent architecture. These distributed entities all report to and receive filtering rules from the single centralized spam agent, merging their detection capabilities while maintaining individual operational independence. This resolves the contradiction by consolidating complexity into a centralized management point while distributing detection functions across the network.
Solution Approach 2:
The centralized spam agent serves multiple functions: it collects spam reports from diverse sources (email, SMS, MMS, IM), analyzes reports from different entity types, generates filtering rules, and distributes rules back to the same diverse entities. This multi-functional design improves spam detection capability across the entire network while using a single versatile component rather than separate specialized systems for each message type.
2Reliability
If spam filtering rules are distributed to multiple entities across the network, then spam blocking effectiveness is improved, but the time required to update and propagate rules increases
Solution Approach 1:
The centralized spam agent generates and prepares spam filtering rules in advance based on analyzed spam reports, storing them ready for distribution. When spam patterns are detected, the agent has pre-computed filtering rules available for immediate propagation to network entities, reducing the time from detection to blocking. This preliminary rule generation resolves the contradiction by preparing defenses before spam campaigns fully propagate.
Solution Approach 2:
The system implements a continuous feedback loop where entities report spam messages to the centralized agent, the agent analyzes reports and generates updated filtering rules, then distributes these rules back to the same entities. This closed-loop feedback mechanism ensures that spam blocking effectiveness continuously improves as the system learns from actual spam patterns, with rule updates propagated rapidly through the established reporting channels.
3Stability of the object's composition
If standardized spam reporting formats are implemented across all network entities, then data consistency is improved, but the implementation complexity and standardization requirements increase
Solution Approach 1:
The centralized spam agent is designed to universally accept spam reports from multiple entity types (message centers, service centers, end user devices) across different messaging platforms (email, SMS, MMS, IM). It implements a unified reporting interface that handles diverse report formats and normalizes them into a consistent internal representation, achieving data consistency while absorbing the implementation complexity within the centralized agent rather than requiring standardization across all distributed entities.
Data Source
AI summary
Systems and methods for spam detection within electronic messages transported over a communication network. One embodiment is a spam center that connects to multiple entities of a communication network that handle electronic messages, such as text messages. The spam center receives spam reports from the entities that detect spam in prior electronic messages, analyzes the spam reports to generate spam filtering rules based on the spam detected in the prior electronic messages. The spam center then distributes the spam filtering rules to one or more of the entities. The entities may then use to spam filtering rules to filter spam out of electronic messages that subsequently received.