Phone Contact List Updates for Vishing Call Blocking

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Solution Overview

Problem

Existing systems fail to effectively identify and block vishing attacks by continuously updating trusted and non-trusted contacts on user devices, allowing scammers to use different phone numbers to evade detection.

Innovation Solution

Implement a system that bulk adds and updates trusted and non-trusted contacts to a user's phone contacts list, using cloud-based services and machine learning algorithms to identify and block or silence calls from non-trusted entities, while allowing calls from trusted ones.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If existing systems use static contact lists to block vishing attacks, then implementation is simple, but the system cannot identify new scam numbers and reliability is low

Engineering Contradiction:

Improvevishing attack detection accuracyVSAvoidcontact update system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary action by proactively obtaining and updating contact lists from multiple third-party sources before vishing attacks occur. The system continuously retrieves updated contact information from credit bureaus, utility companies, and other data sources, then bulk-loads this information onto user devices in advance, enabling devices to recognize and block known scam numbers before they are used in attacks.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediary server that acts as a mediator between multiple data sources and user devices. This intermediary collects contact information from various third-party sources, processes and validates the data, then distributes updated contact lists to users' devices. This intermediary layer simplifies the architecture by centralizing the complex task of aggregating and managing contact information from multiple sources.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If the system continuously updates contact information from multiple sources, then detection accuracy improves, but data processing time and system resources increase

Engineering Contradiction:

Improvecontact identification accuracyVSAvoidcontact list update time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system creates copies of contact information from multiple third-party sources and stores them in a centralized database. When updates are needed, the system retrieves copies of updated contact lists from these sources rather than processing raw data in real-time. This copying approach allows the system to maintain accurate contact information while reducing the computational burden during update operations.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system performs preliminary data retrieval and processing by continuously obtaining contact information from data sources and pre-processing it into a standardized format. This preliminary action completes the heavy lifting of data aggregation and validation before the actual contact list updates are needed, so that when updates occur, the system only needs to transfer and apply pre-processed data, significantly reducing update time.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If the system blocks all unknown numbers, then security improves, but legitimate calls are also blocked and user convenience deteriorates

Engineering Contradiction:

Improvecall blocking accuracyVSAvoiduser calling convenience

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system applies local quality by differentiating between trusted and untrusted contacts at the individual level. Instead of uniformly blocking all unknown numbers, the system marks specific contact entries as trusted based on their presence in updated contact lists from reliable sources. This allows the system to allow calls from known legitimate entities while maintaining blocking for unknown numbers, creating a nuanced, differentiated response based on the specific characteristics of each contact.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system implements feedback mechanisms that allow users to report legitimate callers who may have been blocked, and scammers who managed to bypass filters. This feedback is fed back into the contact list update process, allowing the system to learn from user experiences and adjust its blocking decisions. The feedback loop ensures that the system becomes increasingly accurate over time in distinguishing between legitimate and malicious callers.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12549666B2Computer-based systems and/or computing devices configured for bulk adding and/or updating of trusted and non-trusted contacts to a phone contacts list to prevent vishing; and methods of use thereof

Publication Date: 2026.02.10 CAPITAL ONE SERVICES LLC

AI summary

A method includes generating a set of non-trusted contacts, each contact of the set of non-trusted contacts corresponding to contact information believed to be associated with vishing attacks. The method further includes sending the set of non-trusted contacts to a computing device of a user. The computing device is configured to add the set of non-trusted contacts to a contacts list associated with an audio calling functionality of the computing device. The computing device is configured to receive a call and determine that the call is from a caller associated with a contact in the set of non-trusted contacts. The computing device is configured to silence the call, block the call, or display caller information of the contact based on the determination that the call is from the caller associated with the contact in the set of non-trusted contacts.