Trust Stamp Algorithm for Online Identity Verification
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Solution Overview
Problem
Current identity verification methods for online users are inadequate as they fail to provide quick, inexpensive, and accurate assessments of trustworthiness, often relying on intrusive credit checks or unverified identification documents that do not account for character or social behavior.
Innovation Solution
A method that combines data from public and private databases with social media and e-commerce sources to generate a 'Trust Score' using algorithms that compare and weigh various data points, including biometric data, social media activity, and official records, to provide a numerical rating of trustworthiness, which can be updated and shared through digital badges or URLs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional credit checks and background checks are used to verify trustworthiness, then accuracy of trust assessment may be improved, but cost and time consumption increase significantly
Solution Approach 1:
The system performs preliminary data collection and analysis by gathering information from multiple public sources (social media, e-commerce platforms, professional networks) before a trust verification is needed. This pre-computation allows the trust score to be calculated quickly when requested, resolving the contradiction between thorough assessment and fast delivery.
Solution Approach 2:
Instead of performing expensive and time-consuming traditional background checks, the system creates a digital copy or representation of trustworthiness through a trust score derived from publicly available data. This copy serves as a proxy for the full background check, providing accurate assessment without the associated time and cost penalties.
2Measurement precision
If traditional credit checks and background checks are used to verify trustworthiness, then accuracy of trust assessment may be improved, but expense increases significantly
Solution Approach 1:
The system creates a trust score copy that represents comprehensive background information without requiring expensive traditional credit checks. By using freely available public data from social media, e-commerce platforms, and professional networks, the system provides accurate trust assessment at minimal cost.
Solution Approach 2:
The system uses inexpensive public data sources instead of expensive proprietary credit reporting services. The trust score is generated from low-cost or free data points aggregated from multiple sources, providing accurate assessment without the high expenses associated with traditional background checks.
3Measurement precision
If comprehensive background checks are performed, then trustworthiness assessment accuracy is improved, but intrusiveness and offense to users increases
Solution Approach 1:
The system extracts only the necessary trust-relevant information from public sources without requiring users to provide sensitive personal data. By gathering information from publicly available social media profiles, e-commerce activity, and professional networks, the system achieves accurate trust assessment without intrusive data collection.
Solution Approach 2:
The system uses data that users have already publicly shared themselves through their social media, e-commerce, and professional network activities. No active participation or sensitive information disclosure is required from users, making the process non-intrusive while still gathering comprehensive trust indicators.
4Reliability
If driver's licenses and state ID cards are used for identification, then identity verification is provided, but information security and privacy protection is compromised
Solution Approach 1:
The system extracts only the trust-relevant information from public sources without requiring users to disclose sensitive personal information. By using publicly available data from social media, e-commerce, and professional networks, the system verifies identity and assesses trustworthiness without exposing sensitive data like social security numbers or detailed personal records.
Solution Approach 2:
Instead of requiring users to provide sensitive identification documents, the system creates a digital trust score copy that represents verified identity and trustworthiness. This copy can be shared safely without exposing underlying sensitive personal information, maintaining both verification reliability and privacy protection.
Data Source
AI summary
The present invention relates generally to identity or trustworthiness verification for online users. More specifically, the present invention is a method of identity verification for online users combined with methodologies for evaluating or demonstrating trustworthiness. The present invention may integrate data values from social media, e-commerce, or other sources, which is obtained online into a single accessible report along with information obtained from the subscriber. An algorithm may then calculate these data values or subscriber information to determine its accuracy by comparing these data values with each other and with the subscriber information to generate a rating for the subscriber's trustworthiness with a numerical score referred to herein as a Trust Score or Trust Stamp.