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Artificial Intelligence Adversarial Vulnerability Audit Tool

机译:人工智能对抗漏洞审计工具

摘要

An image with a known, first classification by the machine learning model is received. This image is then iteratively modified using at least one perturbation algorithm and such modified images are input into the machine learning model until such time as the machine learning model outputs a second classification different from the first classification. Data characterizing the modifications to the image that resulted in the second classification can be provided (e.g., displayed in a GUI, loaded into memory, stored in physical persistence, transmitted to a remote computing device). Related apparatus, systems, techniques and articles are also described.
机译:接收具有已知的机器学习模型的初始分类的图像。 然后使用至少一个扰动算法迭代地修改该图像,并且将这种修改的图像输入到机器学习模型中,直到机器学习模型输出与第一分类不同的第二分类。 可以提供对导致第二分类的图像的修改的数据(例如,以GUI显示为存储到存储器,以物理持久性存储到远程计算设备)。 还描述了相关设备,系统,技术和制品。

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