Add to ORKGThe growing dependence on machine learning in real-world applications emphasizes the importance of understanding and ensuring its safety. Backdoor attacks pose a significant security risk due to their stealthy nature and potentially serious consequences. Such attacks involve embedding triggers within a learning model with the intention of causing malicious behavior when an active trigger is present while maintaining regular functionality without it. This paper evaluates the effectiveness of any backdoor attack incorporating a constant trigger, by establishing tight lower and upper boundaries for the performance of the compromised model on both clean and backdoor test data. The developed theory answers a series of fundamental but previously ...
Diffusion models are state-of-the-art deep learning empowered generative models that are trained bas...
Deep learning models achieve excellent performance in numerous machine learning tasks. Yet, they suf...
Backdoor attacks are rapidly emerging threats to deep neural networks (DNNs). In the backdoor attack...
Backdoor attacks mislead machine-learning models to output an attacker-specified class when presente...
Deep neural networks (DNNs) are widely deployed today, from image classification to voice recognitio...
The backdoor or Trojan attack is a severe threat to deep neural networks (DNNs). Researchers find th...
With the success of deep learning algorithms in various domains, studying adversarial attacks to sec...
Backdoor attack is a powerful attack algorithm to deep learning model. Recently, GNN's vulnerability...
Machine learning (ML) has made tremendous progress during the past decade and is being adopted in va...
Textual backdoor attacks are a kind of practical threat to NLP systems. By injecting a backdoor in t...
Deep Neural Networks are well known to be vulnerable to adversarial attacks and backdoor attacks, wh...
We present a novel defense, against backdoor attacks on Deep Neural Networks (DNNs), wherein adversa...
Deep neural networks (DNNs) are known to be vulnerable to both backdoor attacks as well as adversari...
Deep learning has made tremendous success in the past decade. As a result, it is becoming widely dep...
Pre-trained models (PTMs) have been widely used in various downstream tasks. The parameters of PTMs ...
Diffusion models are state-of-the-art deep learning empowered generative models that are trained bas...
Deep learning models achieve excellent performance in numerous machine learning tasks. Yet, they suf...
Backdoor attacks are rapidly emerging threats to deep neural networks (DNNs). In the backdoor attack...
Backdoor attacks mislead machine-learning models to output an attacker-specified class when presente...
Deep neural networks (DNNs) are widely deployed today, from image classification to voice recognitio...
The backdoor or Trojan attack is a severe threat to deep neural networks (DNNs). Researchers find th...
With the success of deep learning algorithms in various domains, studying adversarial attacks to sec...
Backdoor attack is a powerful attack algorithm to deep learning model. Recently, GNN's vulnerability...
Machine learning (ML) has made tremendous progress during the past decade and is being adopted in va...
Textual backdoor attacks are a kind of practical threat to NLP systems. By injecting a backdoor in t...
Deep Neural Networks are well known to be vulnerable to adversarial attacks and backdoor attacks, wh...
We present a novel defense, against backdoor attacks on Deep Neural Networks (DNNs), wherein adversa...
Deep neural networks (DNNs) are known to be vulnerable to both backdoor attacks as well as adversari...
Deep learning has made tremendous success in the past decade. As a result, it is becoming widely dep...
Pre-trained models (PTMs) have been widely used in various downstream tasks. The parameters of PTMs ...
Diffusion models are state-of-the-art deep learning empowered generative models that are trained bas...
Deep learning models achieve excellent performance in numerous machine learning tasks. Yet, they suf...
Backdoor attacks are rapidly emerging threats to deep neural networks (DNNs). In the backdoor attack...