Cheat Detection Using Movement Kinematics and Reaction Time Analysis
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Solution Overview
Problem
Current cheat detection technologies in video games and esports are inadequate in distinguishing between human players and cheaters using bots, particularly advanced cheaters who employ aim bots or trigger bots, as they often mimic human input patterns, making it difficult to differentiate between legitimate pro-level gameplay and cheating.
Innovation Solution
A system and method that compare performance metrics from new players to a validated database of human players, using statistical analysis to determine if the player is human or a cheater by analyzing inputs such as movement kinematics, shot performance, and reaction times, and identifying inconsistencies that indicate cheating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing cheat detection technology is used, then basic cheating can be detected, but advanced cheaters using aim bots or trigger bots cannot be differentiated from human players
Solution Approach 1:
The patent changes the parameters being measured from simple input detection to comprehensive performance metrics including reaction time, movement kinematics, shot timing, and accuracy. By analyzing multiple parameters simultaneously and comparing them against established human performance baselines, the system can detect subtle deviations that indicate bot assistance while maintaining the ability to distinguish legitimate pro-level gameplay.
2Ease of operation
If simple input comparison is used, then detection is easy, but it cannot differentiate between human players and bot-assisted inputs
Solution Approach 1:
The patent segments the analysis into multiple independent components: reaction time measurement, movement kinematics analysis, shot timing evaluation, and accuracy assessment. Each component is analyzed separately against established human performance ranges, allowing the system to maintain operational simplicity while achieving high precision through cumulative analysis of multiple segmented metrics.
3Measurement precision
If performance metrics analysis is implemented, then cheat detection accuracy improves, but system complexity increases
Solution Approach 1:
The system performs self-calibration by establishing performance baselines from aggregated human player data. Once these baselines are established, the system automatically compares new player performance against them without requiring manual intervention or complex configuration. This self-service approach maintains high detection accuracy while minimizing operational complexity.
Data Source
AI summary
A system and method may detect cheating in a computer game, by receiving inputs to a computer game from an entity (which may be a cheater or bot; or a human), comparing the inputs from the entity to data related to inputs to a computer game from human players, and based on the comparing, determining if the entity is a human player or a cheater. The comparing may be based on performance metrics derived from the inputs, and may be by statistical analysis or, comparing a statistical distribution.