Message Abuse Detector Component for Spam Identification
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Solution Overview
Problem
The rise of spam mobile messages in wireless communication networks poses challenges for users and service providers, as existing spam defenses are ineffective in the mobile messaging environment, leading to financial and time-consuming issues for both parties, and misclassification of messages can result in inappropriate actions.
Innovation Solution
A core network component, the Message Abuse Detector Component (MADC), selectively monitors mobile messages, evaluates address information, and applies predefined criteria to identify and classify abusive messages, implementing automated responses such as blocking or crediting users, while also providing users with an abuse reporting mechanism to facilitate accurate classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users contact wireless service providers to report spam messages, then accurate identification of abusive messages is improved, but service provider costs and time consumption increase
Solution Approach 1:
The system enables users to self-report spam messages through a user interface on their mobile devices. Users can initiate abuse reports by interacting with the system interface, providing information about the abusive message without requiring manual intervention from service provider staff. This self-service mechanism reduces time consumption while maintaining identification accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where users receive confirmation that their abuse report has been received and processed. The system also provides feedback by blocking the reported number and notifying the user of the action taken. This feedback loop improves identification accuracy by ensuring user reports are properly processed while reducing time consumption through automated handling.
2Speed
If automated spam detection systems are implemented, then response time is improved, but device complexity increases
Solution Approach 1:
The Message Abuse Detector Component (MADC) is designed as a multi-functional system that handles multiple tasks including monitoring message traffic, detecting abusive content, classifying message types, and executing blocking actions. By consolidating these functions into a single component, the system achieves fast automated response without proportionally increasing overall system complexity.
Solution Approach 2:
The spam detection system is segmented into distinct functional modules within the MADC, including message monitoring, content analysis, classification, and blocking functions. This segmentation allows each module to operate independently and efficiently, improving response time while keeping individual module complexity manageable.
3Measurement precision
If message monitoring and sampling are performed, then accurate classification of abusive messages is improved, but network resources are consumed
Solution Approach 1:
The system performs selective sampling of mobile messages rather than monitoring every single message. By analyzing a representative subset of messages, the system achieves accurate classification of abusive content while reducing the consumption of network resources. The sampling approach allows the MADC to identify spam patterns without requiring full-volume message processing.
4Object-affected harmful factors
If spam messages are blocked automatically, then user protection is improved, but legitimate messages may be blocked (false positives)
Solution Approach 1:
The system applies different blocking strategies based on the specific characteristics of each detected abusive message. Rather than applying a uniform blocking approach, the MADC analyzes message content, sender information, and pattern recognition to determine the appropriate response. This localized quality approach improves user protection by targeting only confirmed spam while reducing false positives that would block legitimate messages.
Solution Approach 2:
The system incorporates feedback mechanisms where users can report received messages as abusive, and the system provides feedback by blocking the reported number and notifying the user. This feedback loop allows the system to learn from user experiences and adjust its blocking decisions, improving both user protection and blocking accuracy by reducing false positives.
Data Source
AI summary
Systems, methods, and devices that identify abusive mobile messages and associated abusive mobile communication device users are presented. A core network can comprise a message abuse detector component (MADC) that can selectively or randomly monitor or sample mobile messages communicated in the core network. The MADC can evaluate origination and destination address information and can identify abusive mobile messages and associated abusive mobile message senders based at least in part on the respective address information and predefined message abuse criteria. The MADC also can distinguish between spam mobile messages, subscription mobile messages, harassing mobile messages, and other mobile messages, and can identify and implement a desired response (e.g., automated response) to the abusive mobile message. To facilitate identifying abusive mobile messages, the MADC also can analyze history and reputation associated with the origination address, reputation of the address reporting an abusive message, message content, etc.