Jan 11, 2023 · The label flipping attack can poison training data resulting in reducing the classification performance of training model.
Jan 11, 2023 · The attack uses agglomerative hierarchical clustering to identify vulnerable samples in training data and then carries out label flipping on ...
As a subclass of poisoning attack, the label flipping attack can poison training data resulting in reducing the classification performance of training model.
The experiments demonstrate that the label flipping attacks impact the performance of ML models. These results can lead to designing more effective and powerful.
A Label Flipping Attack on Machine Learning Model and Its Defense Mechanism ... deep learning model for poison attack and defense. J. Cyber Sec. 5(04), 14 ...
In this paper, we propose a Label Flipping Attack that specifically targets supervised ML-based defenses in the pre- silicon IC design phase. The core of this ...
Mar 5, 2024 · We propose an innovative alarm system that detects the presence of poisoned labels and a defense mechanism designed to uncover the original class labels.
Sep 3, 2024 · The defense mechanism involves evaluating each received model on an auxiliary dataset. Subsequently, the activations of the last layer for ...
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Jan 3, 2023 · We will analyze the robustness of different machine learning models against data poisoning with varying volumes of poisoning data. Index Terms— ...
Label-flipping attacks refer to a class of adversarial attacks that specifically target the labeled data used to train supervised machine learning models.