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Providing the Status of Model Extraction in the Presence of Colluding Users

机译:在存在共谋用户的情况下提供模型提取的状态

摘要

Methods, systems, and computer program products for providing the status of model extraction in the presence of colluding users are provided herein. A computer-implemented method includes generating, for each of multiple users, a summary of user input to a machine learning model; comparing the generated summaries to boundaries of multiple feature classes within an input space of the machine learning model; computing correspondence metrics based at least in part on the comparisons; identifying, based at least in part on the computed metrics, one or more of the multiple users as candidates for extracting portions of the machine learning model in an adversarial manner; and generating and outputting an alert, based on the identified users, to an entity related to the machine learning model.
机译:本文提供了用于在存在共谋用户的情况下提供模型提取的状态的方法,系统和计算机程序产品。一种计算机实现的方法,包括为多个用户中的每个用户生成对机器学习模型的用户输入的摘要;将所生成的摘要与机器学习模型的输入空间内的多个要素类的边界进行比较;至少部分地基于比较来计算对应度量;至少部分地基于所计算的度量,将多个用户中的一个或多个识别为以对抗的方式提取机器学习模型的部分的候选者;根据识别出的用户,生成警报并将其输出到与机器学习模型相关的实体。

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