US-12621354-B2 - System and method for communication validation and multi-attribute trust scoring through cross-network intelligence correlation

US12621354B2US 12621354 B2US12621354 B2US 12621354B2US-12621354-B2

Abstract

A system and method for privacy-preserving communication validation and multi-attribute trust scoring is disclosed. The system analyzes communication metadata to determine pattern legitimacy by comparing current communication patterns against relationship fingerprints without accessing communication content. The system validates relationship context between communicating parties using interaction graph analysis and historical communication data. Cross-network intelligence correlation compares current patterns against aggregated patterns across voice, email, and messaging services, creating a self-strengthening security framework that recognizes emerging threat patterns while validating legitimate communication behaviors. The system generates comprehensive multi-attribute trust assessments comprising individual trust attribute scores including engagement rate, reliability index, channel preference, temporal pattern, and behavioral pattern, combined into overall trust levels. Trust context is displayed through a user interface presenting simplified, intuitive, and actionable information with progressive disclosure capabilities, enabling informed user decisions while preserving privacy. Communication processing actions provide users with appropriate engagement options tailored to specific trust assessment results.

Inventors

Raymond J. Sheppard
Alan W. McCord
Gustavo Manuel Damil Marin

Assignees

ICA AI, Inc.

Dates

Publication Date: 20260505
Application Date: 20251005

Claims (10)

1 . A system for automated affinity-based user acquisition service for service providers, the system comprising: a communication management server comprising one or more processors, a memory, and a plurality of programming instructions stored in the memory, the plurality of programming instructions when executed by the one or more processors causes the one or more processors to: receive an incoming communication directed towards a first user-device among a plurality of user devices; analyze, by a pattern analysis engine, metadata associated with the incoming communication to identify current communication patterns across temporal, channel, and behavioral domains without accessing communication content; compare the current communication patterns against relationship fingerprints stored in a relationship fingerprints database to determine pattern legitimacy; responsive to determining that the current communication patterns are legitimate, validate relationship context between communicating parties using interaction graph analysis and historical communication data; perform cross-network intelligence correlation to identify and validate the current communication patterns, wherein the current communication patterns are compared against aggregated patterns stored in a pattern database across voice, email and messaging services; generate, based on the pattern legitimacy, relationship context validation, and the cross-network intelligence correlation, a multi-attribute trust assessment for the incoming call, wherein the multi-attribute trust assessment comprises generation of individual trust attribute scores and a trust level, wherein the individual trust attribute comprises an engagement rate, a reliability index, a channel preference, a temporal pattern, and a behavioral pattern; and display a trust context derived from the multi-attribute trust assessment through a user interface of the first user device, wherein the trust context comprises simplified trust information that is actionable; and provide communication processing actions for the incoming communication.
2 . The system of claim 1 , wherein the plurality of programming instructions, when executed by the one or more processors, causes the one or more processors to: integrate the individual trust attribute scores and results from the cross-network intelligence to generate the trust level for the incoming communication.
3 . The system of claim 1 , wherein to perform cross-network intelligence correlation, the plurality of programming instructions, when executed by the one or more processors, causes the one or more processors to: perform similarity analysis across email patterns, voice patterns, and SMS patterns; conduct pattern correlation through cross-channel comparison; and validate the current communication patterns by checking consistency of the patterns with known legitimate patterns.
4 . The system of claim 1 , wherein the user interface implements progressive disclosure of trust information with important trust indicators visible immediately and detailed trust attributes available through user interaction.
5 . The system of claim 1 , wherein to validate relationship context, the plurality of programming instructions, when executed by the one or more processors, causes the one or more processors to: wherein validating relationship context comprises: determine relationship strength between the communicating parties based on depth and frequency of past interactions; evaluate connection paths through the interaction graph; and assess alignment with expected relationship behaviors using historical communication data.
6 . The system of claim 1 , wherein the cross-network intelligence correlation enables recognition of emerging threat patterns and validation of legitimate communication behaviors based on collective intelligence while maintaining privacy through pattern-only analysis.
7 . The system of claim 1 , wherein the pattern legitimacy analysis, relationship fingerprint generation, and the cross-network intelligence correlation are performed without accessing communication content.
8 . The system of claim 1 , wherein the actionable trust context translates complex multi-attribute trust assessment into practical user guidance and provides communication processing options tailored to specific trust assessment results.
9 . The system of claim 1 , wherein the individual trust attributes are extracted by pattern analysis engine from the communication metadata.
10 . The system of claim 1 , wherein the individual trust attribute scores are modified based on cross-network intelligence correlation results, wherein consistent patterns result in increasing trust levels.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation-in-part of U.S. patent application Ser. No. 19/298,256, titled, SYSTEM AND METHOD FOR AUTOMATED AFFINITY-BASED NETWORK EXPANSION THROUGH INTELLIGENT RELATIONSHIP DISCOVERY AND COMPATIBILITY MATCHING” filed on Aug. 13, 2025 which claims the benefit of, and priority to, U.S. patent application Ser. No. 18/751,905, titled, U.S. patent application Ser. No. 19/224,748, titled, “SYSTEM AND METHOD FOR MANAGING COMMUNICATION THROUGH SEAMLESS TRANSITIONS BETWEEN SYNCHRONOUS AND ASYNCHRONOUS COMMUNICATIONS” which claims the benefit and priority to U.S. patent application Ser. No. 19/006,192, titled, “SECURITY VALIDATION SYSTEM USING DYNAMIC RELATIONSHIP FINGERPRINTS” filed on Feb. 28, 2025, which claims the benefit, and priority to U.S. patent application Ser. No. 18/921,443, titled, “ADAPTIVE COMMUNICATION MANAGEMENT SYSTEM USING MODEL-BASED AND MODEL FREE REINFORCEMENT LEARNING” filed on Oct. 21, 2024 which claims the benefit of, and priority to, U.S. patent application Ser. No. 18/751,905, titled, “SYSTEMS AND METHOD FOR OPTIMIZING PERSONAL COMMUNICATIONS THROUGH OBJECTIVE ALIGNMENT” which claims the benefit of, and priority to, U.S. Provisional Application No. 63/601,645, titled, “SYSTEM AND METHOD FOR OPTIMIZING PERSONAL COMMUNICATIONS THROUGH OBJECTIVE ALIGNMENT” filed on Nov. 21, 2023, the specifications of which are hereby incorporated by reference in its entirety. BACKGROUND OF THE INVENTION Field of the Art The disclosure relates to the field of communications, and more particularly to the field of validating incoming communication through privacy-preserving pattern analysis and cross-network intelligence sharing. Discussion of the State of the Art Modern communication systems face an epidemic of spoofed calls and messages. Traditional caller ID can be easily manipulated, making it impossible to verify if communications are genuinely from claimed sources. Scammers routinely impersonate banks, government agencies, and trusted contacts. Existing security systems provide only crude “trusted/untrusted” classifications that fail to capture the nuanced nature of human relationships. A business contact calling after hours might be legitimate but unusual, yet current systems cannot distinguish this from a potential threat. Moreover, existing security systems may require access to communication content, personal information, or behavioral data, forcing users to sacrifice privacy for security. Content monitoring systems analyze message text, identity verification requires personal data collection, and behavioral analysis tracks usage patterns in privacy-invasive ways. Additionally, the situation is further complicated by the siloed nature of existing security systems that perform validation of communication within specific channels (email, voice, messaging) or services, unable to leverage insights across different communication methods. A sophisticated attack might use consistent patterns across multiple channels, but fragmented systems cannot detect these coordinated threats. Furthermore, from a user perspective the current security systems provide minimal context information about incoming communications, forcing users to make communication decisions without any information. This may lead to missed important communications, acceptance of risky contacts, or privacy violations that undermine user trust in the security system itself. Hence, there is a need for security systems that provide context to users to make communication decisions without accessing compromising privacy. SUMMARY OF THE INVENTION Accordingly, the inventor has conceived and reduced to practice, in a preferred embodiment of the invention, a system and method for privacy-preserving communication validation and multi-attribute trust scoring that transforms complex communication pattern analysis into actionable user guidance while maintaining privacy protection. The system implements a communication management server comprising one or more processors, a memory, and programming instructions that analyze communication metadata to determine pattern legitimacy by comparing current communication patterns against relationship fingerprints stored in a relationship fingerprints database without accessing communication content. When current communication patterns are determined legitimate, the system validates relationship context between communicating parties using interaction graph analysis and historical communication data, performs cross-network intelligence correlation across voice, email, and messaging services, and generates comprehensive multi-attribute trust assessments comprising individual trust attribute scores and overall trust levels. The system displays trust context through a user interface presenting simplified, intuitive, and actionable information while providing communication processing actions tailored to specific trust assessment results. According to a preferred e