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Projected Vector Modification as Mitigation for Machine Learning Model String Stuffing
Projected Vector Modification as Mitigation for Machine Learning Model String Stuffing
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机译:预计矢量修改为机器学习模型串填充的缓解
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摘要
An artifact is received from which features are extracted so as to populate a vector. The features in the vector can be reduced using a feature reduction operations to result in a modified vector having a plurality of buckets. A presence of predetermined types of features are identified within buckets of the modified vector influencing a score above a pre-determined threshold. A contribution of the identified features within the high influence buckets of the modified vector is then attenuated. The modified vector is input into a classification model to generate a score which can be provided to a consuming application or process. Related apparatus, systems, techniques and articles are also described.
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