Caller Identity Verification via Notification App Icon Updates
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Solution Overview
Problem
Existing technologies face challenges in effectively verifying the identity of communication sources, particularly in preventing fraudulent activities such as vishing and spam calls, where caller ID information is often spoofed.
Innovation Solution
The implementation of a computer-implemented method involving caller identity verification and notification, which includes configuring a notification application to transmit indications of incoming calls, using machine learning models to determine the likelihood of a call being from a legitimate or fraudulent entity, and updating application icons on receiving devices to indicate the verified identity of the caller.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional caller ID verification is used, then the system is simple and easy to operate, but it cannot effectively detect spoofed caller identities and fraudulent activities
Solution Approach 1:
The patent introduces an intermediary notification application that acts as a mediator between the calling device and the receiving device. This application intercepts outgoing calls, analyzes caller ID information, and sends notifications to the receiving device about the authenticity of the incoming call. The intermediary layer enables sophisticated fraud detection without requiring complex changes to the core telephony system.
Solution Approach 2:
The notification application performs preliminary analysis of caller identity before the call is actually received. By analyzing the caller ID, checking against known fraudulent patterns, and sending advance notifications to users, the system prepares users to recognize potential fraud before the call connects, thereby improving verification reliability without adding complexity during the actual call process.
2Measurement precision
If machine learning models are implemented for call verification, then the accuracy of detecting fraudulent calls is improved, but the computational resources and processing time are increased
Solution Approach 1:
The notification application implements partial machine learning analysis by focusing only on key features of caller ID information and call patterns that are most indicative of fraud. Rather than analyzing all possible call parameters, the system applies ML models selectively to the most relevant data points, maintaining high detection accuracy while reducing computational energy consumption.
3Reliability
If visual indicators are added to application icons to show caller authenticity, then user awareness of call legitimacy is improved, but the interface complexity and development effort are increased
Solution Approach 1:
The notification application uses color changes on application icons to indicate caller authenticity. Legitimate calls are marked with green indicators, while potentially fraudulent calls show red or yellow warnings. This visual coding system provides immediate, intuitive information to users without requiring complex interface elements, maintaining simplicity while significantly improving user ability to identify legitimate calls.
Data Source
AI summary
Systems and methods of caller identity verification and notification are disclosed. In one embodiment, an exemplary computer-implemented method may include: configuring a notification application, executing at a first computing device associated with a first user, the first user associated with an entity; receiving, from the notification application executing on the first computing device, an indication when the first user initiates a particular call to a second user; determining an application associated with the entity and installed on the second computing device of the second user, the application having an icon displayed at a screen of the second computing device; and instructing the application, executing on the second computing device, when the second computing device has received the particular call from the first user, to update an appearance of the icon associated with the application to display an indicator with regard to that the first user is associated with the entity.