Silent Network Authentication for Secure Personalized RCS Messaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing online transactions face security challenges due to increased fraud and cumbersome user experiences from static web content, leading to reduced trust and willingness to conduct transactions via networks.
Innovation Solution
Implementing a system that generates customized Rich Communication Service (RCS) messages using machine learning to deliver personalized content, including interactive elements, based on user behavior and preferences, while ensuring secure authentication through Silent Network Authentication (SNA) protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static web content is used for all visitors, then scalability and ease of operation are improved, but user experience and relevance deteriorate
Solution Approach 1:
The system pre-generates multiple customized webpage versions tailored to different user profiles, behaviors, and preferences before the user actually visits. When a user arrives, the system quickly selects and serves the pre-prepared customized version that best matches their characteristics, eliminating the need for real-time customization while still delivering personalized content.
Solution Approach 2:
Instead of creating unique customized webpages for each user from scratch, the system creates templates and copies of standardized webpage structures, then applies personalized elements (such as different content blocks, layouts, or recommendations) to these copies based on user profiles. This allows rapid generation of customized pages while maintaining scalability.
2Reliability
If traditional authentication methods are used, then security verification is achieved, but user convenience and transaction speed deteriorate
Solution Approach 1:
The system performs authentication automatically in the background without requiring active user participation. The user's device continuously provides authentication credentials (such as device identifiers, biometric data, or cryptographic keys), and the system silently verifies these credentials throughout the transaction process, eliminating the need for manual login steps while maintaining strong security.
Solution Approach 2:
Authentication credentials are established and verified in advance before the actual transaction occurs. The system performs preliminary authentication checks when the user first accesses the service, establishing trust beforehand. This allows subsequent transactions to proceed more quickly with reduced friction, as the foundational security verification has already been completed.
3Adaptability or versatility
If customized webpages are generated in real-time, then personalization and user experience are improved, but system complexity and processing time increase
Solution Approach 1:
The system pre-generates multiple customized webpage versions tailored to different user profiles, behaviors, and preferences before the user actually visits. When a user arrives, the system quickly selects and serves the pre-prepared customized version that best matches their characteristics, eliminating the need for real-time customization while still delivering personalized content.
Solution Approach 2:
The webpage customization system is divided into modular segments or components (such as header, content blocks, sidebar, footer) that can be independently configured and assembled. Each segment can be pre-prepared and stored separately, then quickly combined based on user preferences. This segmentation reduces the complexity of generating fully customized pages from scratch while maintaining personalization capabilities.
Data Source
AI summary
Systems and methods are described for receiving a request to provide content to at least one authorized recipient; generating a customized message comprising at least one action associated with the content; causing transmission of the customized message to a mobile computing device associated with the at least one authorized recipient, requesting authorization data corresponding to the at least one authorized recipient; responsive to receiving the requested authorization data: verifying that the authorization data correlates to an identity of the at least one authorized recipient or an identity of the mobile computing device; determining a classification of the at least one authorized recipient; and generating a Rich Communication Service (RCS) message comprising the content; and scheduling, using a machine learning model and based on the determined classification, delivery of the RCS message to the mobile computing device.


