Trust Network Model for Entity Trustworthiness Assessment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In today's digital world, there is a lack of effective methods to distinguish between fraudulent and truthful information, and to establish trust between entities and in information, due to digital anonymity and uncertainty in identity.
Innovation Solution
A computer-implemented method and system for determining trustworthiness by generating a model based on nodes associated with an entity, where each node corresponds to additional entities defined by trust metrics, relationship indications, and activation functions, and using this model to generate an aggregated trust metric and graphical views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital anonymity is maintained to protect privacy, then entity privacy is preserved, but trust establishment between entities deteriorates
Solution Approach 1:
The patent introduces a trust network as an intermediary system that mediates between entities seeking to establish trust while maintaining their anonymity. The trust network contains nodes representing entities and relationships between them, allowing trust assessment without direct identity disclosure. This resolves the contradiction by enabling trust establishment (improving reliability) through the intermediary trust network while preserving digital anonymity (avoiding worsened identity verification complexity).
Solution Approach 2:
The patent transforms the trust assessment problem by changing parameters from direct identity verification to indirect trust metric evaluation. Instead of verifying identities directly (which would compromise anonymity), the system evaluates trustworthiness through computed trust metrics derived from network relationships, entity behaviors, and historical interactions. This parameter change enables trust establishment while maintaining the anonymity required for privacy protection.
2Measurement precision
If comprehensive verification tools are used to establish trust, then trust accuracy is improved, but operational complexity increases
Solution Approach 1:
The trust network system performs self-service by automatically computing trust metrics and assessing entity trustworthiness without requiring manual verification operations. The system autonomously evaluates relationships between nodes, processes entity behaviors, and generates trust assessments through predefined algorithms. This resolves the contradiction by improving trust assessment accuracy through comprehensive automated verification while maintaining ease of operation, as users simply query the system rather than performing complex verification procedures.
Solution Approach 2:
The system performs preliminary actions by pre-computing and storing trust metrics, relationship data, and entity profiles in the trust network before trust assessments are needed. This preliminary preparation enables rapid, accurate trust evaluations when requested, resolving the contradiction between measurement precision (improved through comprehensive pre-computed data) and ease of operation (improved through quick query responses without manual verification steps).
Data Source
AI summary
Systems and methods are described for determining trustworthiness. The systems and methods may perform obtaining a plurality of nodes associated with a first entity, wherein the plurality of nodes correspond to one or more additional entities, each of the one or more additional entities being defined by a trust metric, a relationship indication, and at least one activation function, generating, for each of the plurality of nodes, an output by executing each activation function according to a set of predefined rules defined for the plurality of nodes, wherein each activation function uses a respective trust metric defined for the one or more additional entities, and generating a model for determining trustworthiness of the first entity based on each relationship indication and the output for each of the plurality of nodes.