Adaptive anti-cheating method for multi-dimensional behavioral fingerprinting

By collecting multi-dimensional behavioral fingerprint data and fusing real-time features, combined with dynamic adjustment and hierarchical intervention, the problem of insufficient adaptability in existing anti-cheating methods has been solved. This has enabled accurate identification of cheating behavior and stability of the assessment process, improving the accuracy of cheating identification and user experience.

CN122113076APending Publication Date: 2026-05-29BEIJING WAIYAN ONLINE DIGITAL TECH CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING WAIYAN ONLINE DIGITAL TECH CO LTD
Filing Date
2026-02-03
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

In existing technologies, anti-fraud methods based on multidimensional behavioral fingerprint analysis lack an integrated, end-to-end adaptive control loop, resulting in low overall performance and practicality, making it difficult to cope with complex fraudulent methods. Furthermore, traditional verification methods affect user experience and process continuity.

Method used

By collecting multi-dimensional behavioral fingerprint data and fusing real-time features, the risk index is dynamically adjusted, and hierarchical intervention and adaptive regulation are implemented. Combined with an interactive verification interface and token-based authentication, the system can accurately identify and differentiate cheating behaviors.

Benefits of technology

It achieves comprehensive and accurate perception of user behavior, improves the accuracy of cheating behavior identification and system fault tolerance, ensures the stability of the assessment process and the authenticity of data, and takes into account the answering experience of normal users.

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Abstract

The application discloses a multi-dimensional behavior fingerprint analysis adaptive anti-cheating method. The method relates to the technical field of adaptive anti-cheating and comprises the following steps: behavior data acquisition and monitoring, real-time risk analysis and decision-making, adaptive challenge generation and interaction, and tokenization state recovery and submission. The application collects multi-dimensional behavior fingerprint data of user answers in real time, obtains a real-time risk index through feature fusion, judges whether to intervene in grading, then issues a verification instruction according to the index and renders a corresponding verification interface, generates a one-time token after the user passes the verification, reissues a submission request combined with the temporary examination data to complete the examination submission, improves the overall performance and practicability of the multi-dimensional behavior fingerprint analysis anti-cheating method, and solves the problem of low overall performance and practicability of the multi-dimensional behavior fingerprint analysis anti-cheating method due to the lack of an integrated, end-to-end adaptive regulation closed loop in the prior art.
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