Server Interaction Detection via Credit Rating Verification
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Solution Overview
Problem
Conventional interaction detection technologies, especially collision detection in servers, consume excessive CPU resources and pose security risks when relying solely on client terminal verification without further validation.
Innovation Solution
A computer system that determines a credit rating for interaction information from client terminals, broadcasting verified interactions and downgrading unverified ones, thereby reducing server burden and enhancing security by utilizing a threshold-based verification process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the server conducts bounding box interaction detection, then interaction detection accuracy is improved, but CPU resource consumption increases excessively
Solution Approach 1:
The patent segments the interaction detection process into two parts: client-side preliminary detection using simplified algorithms, and server-side verification only for suspicious cases. This division reduces the server's computational burden while maintaining detection accuracy through selective detailed analysis.
Solution Approach 2:
The server performs full bounding box detection only partially - specifically, only for interactions that fail the client-side preliminary check or meet certain verification conditions. For other interactions, the server trusts the client's detection results, thus avoiding excessive computational action while maintaining security.
2Productivity
If the server directly adopts client terminal interaction detection results, then server computational burden is reduced, but security risks increase
Solution Approach 1:
The system implements a feedback mechanism where the server sends verification requests back to the client for specific interactions. Based on the client's response and the interaction's credibility score, the server decides whether to accept or reject the interaction result, thus maintaining security while improving efficiency.
Solution Approach 2:
The patent introduces a credibility score parameter that dynamically changes based on client behavior history. This parameter determines the level of verification required - high-credibility clients experience faster processing with minimal verification, while low-credibility clients undergo stricter checking, thus balancing efficiency and security adaptively.
3Reliability
If the server verifies all interaction information, then security is improved, but data processing burden increases
Solution Approach 1:
The client performs preliminary interaction detection and filtering before sending data to the server. This preliminary action reduces the volume of data requiring server verification, allowing the server to focus computational resources on verifying only the most critical or suspicious interactions rather than all interactions.
Solution Approach 2:
The patent extracts and removes obviously valid interactions from the verification queue by using client-side pre-validation. Only interactions that fail client-side checks or meet specific risk criteria are extracted for server verification, thus reducing the overall processing burden while maintaining security for problematic cases.
Data Source
AI summary
The current invention discloses devices and methods that may be used for detection and verification of interactions, such as collisions, between objects in application programs, such as online games. After receiving interaction information from a first terminal, a server may send the interaction information to another terminal for verification based on the first terminal's credit rating. When the credit rating is high, the server may broadcast the interaction information before the verification process, which may be conducted randomly. On the other hand, when the credit rating is low, the server may wait for the verification results from the other terminal and only broadcast the interaction information when the information is confirmed. Such an approach optimizes the interaction verification process, reduces security risk, and saves computing resources.