Software Usage Validation Using Activity Similarity Checks
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Solution Overview
Problem
Existing play-to-earn game software systems are vulnerable to cheating, as they lack effective methods to validate the duration of game play, allowing players to unfairly manipulate rankings and rewards through replay uploads, idling, or using bots.
Innovation Solution
Implement a system using a Neural Network Black Box (NNBB) and Verifiable Delay Function (VDF) to verify user game play time, combined with blockchain network validation, ensuring timestamps are authentic and user activity is genuine, preventing cheating by analyzing biometric and gameplay data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If play-to-earn game software uses APIs to collect data and determine rewards based on performance, then rewards can be distributed automatically, but the system becomes vulnerable to cheating through replay uploads, idling, or bot usage
Solution Approach 1:
A validation node is introduced as an intermediary component between the game software and the reward distribution system. This validation node captures gameplay data, verifies its authenticity through multiple validation dimensions (biometric verification, gameplay behavior analysis, anti-cheat detection), and only validates genuine gameplay before triggering rewards. This intermediary layer filters out cheating attempts while maintaining automated reward distribution.
2Reliability
If the system validates gameplay time and authenticity, then cheating is reduced, but the validation process adds complexity to the system architecture
Solution Approach 1:
The validation system is segmented into independent validation modules, each responsible for a specific validation dimension: biometric verification module, gameplay behavior analysis module, anti-cheat detection module, and time validation module. Each module operates independently and can be validated separately, reducing the complexity of the overall system while maintaining comprehensive validation coverage.
3Reliability
If multiple validation dimensions are implemented for gameplay verification, then cheating detection improves, but the validation time and processing requirements increase
Solution Approach 1:
The system performs preliminary validation actions by pre-configuring validation rules, thresholds, and detection parameters before gameplay occurs. Validation nodes are pre-loaded with anti-cheat detection algorithms and validation criteria, enabling rapid verification during gameplay without requiring complex real-time computation, thus reducing validation time while maintaining high detection accuracy.
Data Source
AI summary
A method and an apparatus for validating software usage are described. The method involves collecting data containing user activity data when a piece of software is running and being used by a user, periodically generating a data packet containing the data collected to obtain a plurality of the data packets; verifying that each data packet is generated according to predetermined rules, checking the collected data contained in a plurality of verified data packets to determine whether the user is using the software, and checking whether the checked collected data have similarity with past collected data that exceeds a predetermined level of similarity. Software usage by a user is deemed to be validated if it is determined that the user is using the software and no past collected data exceeding the predetermined level of similarity is found.