Search Results for author:
Found 5 papers, 1 papers with code
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.
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.
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.
Modeling Attack Resilient Reconfigurable Latent Obfuscation Technique for PUF based Lightweight Authentication
Physical unclonable functions (PUFs), as hardware security primitives, exploit manufacturing randomness to extract hardware instance-specific secrets.
Cryptography and Security
