Client Session Trust Calculation via Proof of Work Feedback
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Solution Overview
Problem
Existing online systems face challenges in distinguishing between real user interactions and simulated user activities, such as bots, which can lead to resource abuse and impact the legitimacy of view counting for online media content, as illegitimate users aim to emulate large numbers of legitimate users with minimal computing resources.
Innovation Solution
A system calculates the trustworthiness of client sessions by receiving a proof of work value based on a work function and inputs from connected services, determining a probability of trustworthiness, and providing feedback to update the work function, thereby increasing the complexity and reducing the economic viability of creating illegitimate sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system accepts all client sessions without verification, then the system operates with minimal complexity and fast processing, but illegitimate sessions can abuse resources and corrupt view counting accuracy
Solution Approach 1:
The system performs preliminary work by pre-distributing puzzle pieces to clients before they need to prove their legitimacy. This preliminary action allows the system to verify sessions efficiently without complex real-time computation, as clients must have received and processed the puzzle pieces to generate valid proofs.
Solution Approach 2:
The patent introduces puzzle pieces as an intermediary mechanism between the service provider and clients. These puzzle pieces act as a mediator that clients must process to generate proofs of work, enabling verification without direct complex interaction between the system and each client session.
2Measurement precision
If the system implements a proof of work verification mechanism, then the accuracy of distinguishing legitimate from illegitimate sessions improves, but the computational complexity and processing time for each session increases
Solution Approach 1:
The system performs preliminary work by pre-distributing puzzle pieces to clients before they need to prove their legitimacy. This preliminary action allows the system to verify sessions efficiently without complex real-time computation, as clients must have received and processed the puzzle pieces to generate valid proofs.
Solution Approach 2:
The patent implements a probabilistic verification approach where the system can choose to verify a subset of sessions or adjust the strictness of verification based on risk assessment. This partial action approach reduces overall verification time while maintaining sufficient accuracy by focusing computational resources on high-risk sessions.
3Reliability
If the system requires proof of work calculation from each client session, then the ability to detect illegitimate sessions improves, but the computational resources required from the system increase
Solution Approach 1:
The patent introduces puzzle pieces as an intermediary mechanism between the service provider and clients. These puzzle pieces act as a mediator that clients must process to generate proofs of work, enabling verification without direct complex interaction between the system and each client session.
Solution Approach 2:
The system shifts computational burden to clients by requiring them to perform proof of work calculations on puzzle pieces they receive. This self-service approach allows clients to demonstrate their legitimacy through their own computational effort, reducing the energy burden on the service provider's systems.
4Adaptability or versatility
If the system uses a static verification method, then the implementation is simple and fast, but it cannot adapt to evolving bot techniques and remains vulnerable to new types of abuse
Solution Approach 1:
The patent implements a dynamic verification system where puzzle pieces can be updated, regenerated, and distributed differently to various clients. The verification methodology adapts to new bot techniques by changing the puzzle characteristics rather than redesigning the entire verification system, maintaining simplicity while improving adaptability.
Data Source
AI summary
Described herein is a system for calculating trust of a client session. A proof of work value is received from a session of a client computer. The proof of work value is calculated by the session of the client computer based, at least in part, upon a work function and input(s) received from service(s) connected to the session. A probability that the session is trustworthy is calculated based, at least in part, upon the proof of work value. Feedback is provided to the session of the client computer based, at least in part, upon the calculated probability. The feedback can increase complexity or frequency of calculation. The feedback can include an update to the work function.


