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Revealing Backdoors, Post-Training, In Dnn Classifiers Via Novel Inference On Optimized Perturbations Inducing Group Misclassification
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Revealing Backdoors, Post-Training, In Dnn Classifiers Via Novel Inference On Optimized Perturbations Inducing Group Misclassification
Recently, a special type of data poisoning (DP) attack against deep neural network (DNN) classifiers, known as a backdoor, was proposed. These attacks do not seek to degrade classification accuracy, but rather to have the classifier learn to classify to a
Recently, a special type of data poisoning (DP) attack against deep neural network (DNN) classifiers, known as a backdoor, was proposed. These attacks do not seek to degrade classification accuracy, but rather to have the classifier learn to classify to a
