A logic side AI meme virus detection method based on information entropy change and weighted model

The logic-side AI meme virus detection method based on information entropy change and weighted model solves the problem of meme virus identification and defense in logic-side AI, achieving high-precision detection and low false positive rate and flexible defense, thus improving the stability and security of the system.

CN122241702APending Publication Date: 2026-06-19于翔升
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
于翔升
Filing Date
2026-03-25
Publication Date
2026-06-19

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Abstract

This invention discloses a logic-side AI meme virus detection method based on information entropy change and a weighted model, belonging to the field of artificial intelligence security. This method preprocesses the input text, calculates the source uncertainty entropy, logical disorder entropy, and system state stability coefficient, uses a weighted model to obtain an isolation boundary value, and compares it with a preset threshold to determine risk. This invention employs a flexible defense mechanism of "checking but not eliminating," dynamically adjusting weights and continuously optimizing the model, effectively improving the accuracy and adaptability of meme virus detection, and is suitable for security protection of various logic-side AI systems.
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