API Metadata Bot Detection via Segmentation
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Solution Overview
Problem
Online gaming systems face challenges in detecting cheating players who use sophisticated bots, as these bots mimic human behavior, making it difficult to distinguish between human and automated gameplay, which undermines fair play and player experience.
Innovation Solution
A bot detection system that utilizes API data analysis and machine learning models to identify cheating by generating API metadata from player interactions, which is then applied to trained bot detection models to determine if a player is using a bot, and enforces actions such as banning or slowing down the player account if detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional bot detection methods are used, then detection simplicity is maintained, but detection accuracy deteriorates as bots become more sophisticated
Solution Approach 1:
The patent segments bot detection into multiple independent analysis components: API call pattern analysis, input device signal analysis, gameplay behavior analysis, and statistical anomaly detection. Each component processes specific aspects of player behavior separately, then combines results for comprehensive detection. This modular approach maintains accuracy while managing system complexity.
Solution Approach 2:
The patent transitions from traditional single-dimension detection (e.g., response time only) to multi-dimensional analysis by examining API call patterns, input device signals, gameplay behaviors, and statistical metrics simultaneously. This dimensional expansion enables accurate detection of sophisticated bots that mimic human behavior in traditional detection areas.
2Measurement precision
If sophisticated bot detection analysis is implemented, then bot detection accuracy improves, but processing time increases
Solution Approach 1:
The patent performs preliminary analysis of API call patterns and gameplay behaviors during normal game operation, building statistical baselines and detecting anomalies in real-time. This preliminary detection allows the system to flag suspicious activities for more intensive analysis only when needed, reducing overall processing time while maintaining high accuracy.
Solution Approach 2:
The patent implements a tiered detection approach where the system quickly processes obvious cases using simplified rules (skipping detailed analysis for clear-cut situations) and reserves comprehensive multi-dimensional analysis for borderline cases. This allows the system to maintain high throughput while ensuring accurate detection of sophisticated bots.
3Measurement precision
If API data analysis is performed on all player interactions, then cheating detection accuracy improves, but system computational load increases
Solution Approach 1:
The patent applies different levels of analysis intensity to different players based on their behavior patterns. Players with normal gameplay patterns receive minimal processing, while those exhibiting suspicious behaviors trigger more intensive API data analysis. This localized quality adjustment maintains high detection accuracy while significantly reducing overall computational energy consumption.
Solution Approach 2:
The patent dynamically adjusts analysis parameters such as sampling rates, data retention periods, and detection thresholds based on game context, player history, and suspected cheating levels. This parameter optimization enables accurate cheating detection while minimizing unnecessary computational energy expenditure on low-risk players.
Data Source
AI summary
A bot detection system and method analyzes application programming interface (API) data associated with an online gaming player account to make a determination of whether the player account is engaging in cheating by using a bot during online game play. The API data may be analyzed to generate API metadata that is descriptive of the API data, such as an indication of how many API calls were made to a particular API during a particular time period on behalf of the player account. The API data may be applied to one or more bot detection models to make an assessment of whether the player account is using a bot. If bot usage is detected with a player account, enforcement actions, such as slowing down game play or banning the player account, may be implemented for that player account.