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Found 10 papers, 2 papers with code
Watch Out! Simple Horizontal Class Backdoors Can Trivially Evade Defenses
In VCB attacks, any sample from a class activates the implanted backdoor when the secret trigger is present.
CIT-EmotionNet: CNN Interactive Transformer Network for EEG Emotion Recognition
Emotion recognition using Electroencephalogram (EEG) signals has emerged as a significant research challenge in affective computing and intelligent interaction.
Vertical Federated Learning: Taxonomies, Threats, and Prospects
In a number of practical scenarios, VFL is more relevant than HFL as different companies (e. g., bank and retailer) hold different features (e. g., credit history and shopping history) for the same set of customers.
TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World
We observe that the backdoor effect of both misclassification and the cloaking are robustly achieved in the wild when the backdoor is activated with inconspicuously natural physical triggers.
Towards A Critical Evaluation of Robustness for Deep Learning Backdoor Countermeasures
Since Deep Learning (DL) backdoor attacks have been revealed as one of the most insidious adversarial attacks, a number of countermeasures have been developed with certain assumptions defined in their respective threat models.
Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World
The averaged ASR still remains sufficiently high to be 78% in the transfer learning attack scenarios evaluated on CenterNet.
NTD: Non-Transferability Enabled Backdoor Detection
A backdoor deep learning (DL) model behaves normally upon clean inputs but misbehaves upon trigger inputs as the backdoor attacker desires, posing severe consequences to DL model deployments.
Quantization Backdoors to Deep Learning Commercial Frameworks
This work reveals that the standard quantization toolkits can be abused to activate a backdoor.
RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things
To this end, a 1-bit quantized DNN model or deep binary neural network maximizes the memory efficiency, where each parameter in a BNN model has only 1-bit.
Dynamic Coronary Roadmapping via Catheter Tip Tracking in X-ray Fluoroscopy with Deep Learning Based Bayesian Filtering
The proposed roadmapping and tracking approaches were validated on clinical X-ray images, achieving accurate performance on both catheter tip tracking and dynamic coronary roadmapping experiments.
