Digital Journey Trust Scoring for Bot-Resistant Visitor Validation
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Solution Overview
Problem
Existing digital marketing campaigns suffer from significant ad-fraud due to bots mimicking human interactions, leading to inflated impressions and clicks, resulting in substantial financial losses for advertisers, and current solutions are inadequate against sophisticated bot technologies.
Innovation Solution
A user journey validation system utilizing a fully distributed blockchain computer system, trust network, digital journey mapping, and AI analysis to dynamically assess visitor trustworthiness by recording and analyzing digital interactions, detecting bot-like behavior, and updating trust scores in real-time to prevent fraudulent access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If server-side logs or network traffic analysis is used to detect ad-fraud, then some fraudulent activity can be identified, but the solution is easily bypassed by sophisticated bot technology
Solution Approach 1:
The system performs preliminary validation by analyzing the visitor's digital journey and behavior patterns before the ad interaction occurs. Trust scores are calculated in advance based on multiple data points from the visitor's online behavior, so when the ad click happens, the validation is already complete and cannot be bypassed by bot technology at the moment of interaction.
Solution Approach 2:
The patent introduces an intermediary validation layer between the visitor and the ad platform. Instead of directly analyzing server logs or network traffic, the system uses a trust score mechanism that mediates the validation process by aggregating multiple behavioral indicators into a single reliability metric that is difficult for bots to replicate.
2Measurement precision
If a comprehensive digital journey mapping system is implemented to validate visitors, then visitor trustworthiness can be accurately assessed, but the system complexity increases
Solution Approach 1:
The system changes parameters by transforming complex multi-dimensional visitor behavior data into a single standardized trust score parameter. This allows accurate assessment of visitor trustworthiness while simplifying the output for integration into ad validation systems, effectively managing complexity through parameter transformation.
3Reliability
If real-time analysis of digital journeys is performed to detect bot behavior, then fraudulent visitors can be identified, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of visitor digital journeys and calculates trust scores before the ad interaction occurs. This advance processing ensures that when the actual validation is needed, the analysis is already complete, eliminating delays during critical ad interaction moments while maintaining high detection accuracy.
Data Source
AI summary
The present invention relates to a user digital journey validation method comprising the steps of: connecting, by a fully distributed blockchain computer system, a trust network comprising: a plurality of user nodes; a plurality of trusted party nodes; a visitor node corresponding to a visitor to a digital service; and a plurality of links, the user nodes corresponding to users, the trusted party nodes corresponding to trusted parties, the visitor node being the most recent node in the trust network, the links being the connections between nodes; rating, by the trust network, the visitor node, the rating being a visitor trust score; recording, via a digital journey mapping system, a digital journey of the visitor; analysing, by the AI system, the digital journey of the visitor; detecting, by the AI system, bot-like behaviour associated with the visitor node or the user nodes; assigning, by the AI system, a warning flag to the visitor node or the user if the visitor node or user node has associated bot-like behaviour; removing, by the AI system, any fraudulent nodes in the trust network, the fraudulent nodes being user nodes or visitor nodes having associated warning flags; updating, by the trust network, the visitor trust score based on the analysis results of the digital journey and the removal of any links connected to or from fraudulent nodes; and providing, by the AI system, a signal or value indicative of a degree of trustworthiness, to the digital service. The present invention aims to provide a means of validating whether a visitor of a digital service is a human.