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ADVERSARIAL ATTACK ON BLACK BOX OBJECT DETECTION ALGORITHM

机译:黑匣子对象检测算法中的攻击

摘要

Systems and methods to generate an adversarial attack on a black box object detection algorithm of a sensor involve obtaining an initial training data set from the black box object detection algorithm. The black box object detection algorithm performs object detection on initial input data to provide black box object detection algorithm output that provides the initial training data set. A substitute model is trained with the initial training data set such that output from the substitute model replicates the black box object detection algorithm output that makes up the initial training data set. Details of operation of the black box object detection algorithm are unknown and details of operation of the substitute model are known. The substitute model is used to perform the adversarial attack. The adversarial attack refers to identifying adversarial input data for which the black box object detection algorithm will fail to perform accurate detection.
机译:对传感器的黑匣子对象检测算法产生对抗攻击的系统和方法涉及从黑匣子对象检测算法获得初始训练数据集。黑盒对象检测算法对初始输入数据执行对象检测,以提供提供初始训练数据集的黑盒对象检测算法输出。用初始训练数据集训练替代模型,以便替代模型的输出复制组成初始训练数据集的黑匣子对象检测算法输出。黑盒物体检测算法的操作细节是未知的,并且替代模型的操作细节是已知的。替代模型用于执行对抗攻击。对抗攻击是指识别黑箱对象检测算法将无法执行准确检测的对抗输入数据。

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