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Showing 1 to 4 of 4 for “"Backdoor Attack"”.

  1. Exploring the landscape of backdoor attacks on deep neural network models

    … recently been demonstrated to be vulnerable to backdoor attacks. Specifically, by introducing a small set of training inputs, an adversary is able to plant a backdoor in the trained model that enables them to fully control the model's behavior during inference. In this thesis, the landscape of …

    mit Repository record for Exploring the landscape of backdoor attacks on deep neural network models (opens in a new tab)

  2. TextGuard: Provable defense against backdoor attacks on text classification

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01

    uiuc Repository record for TextGuard: Provable defense against backdoor attacks on text classification (opens in a new tab)

  3. Trustworthy machine learning throughout model’s life cycle

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms

    uiuc Repository record for Trustworthy machine learning throughout model’s life cycle (opens in a new tab)

  4. Defending Against Trojan Attacks on Neural Network-based Language Models

    Backdoor (Trojan) attacks are a major threat to the security of deep neural network (DNN) models. They are created by an attacker who adds a certain pattern to a portion of given training dataset, causing the DNN model to misclassify any inputs that contain the pattern. These infected classifiers …

    vt Repository record for Defending Against Trojan Attacks on Neural Network-based Language Models (opens in a new tab)