419 citations · 587 across the 8 of their papers we have counts for
8 papers
Natural Backdoor Attacks on Speech Recognition Models
Jinwen Xin, Xixiang Lyu, Jing Ma
With the rapid development of deep learning, its vulnerability has gradually emerged in recent years. This work focuses on backdoor attacks on speech recognition systems. We adopt…
Backdoor Token Unlearning: Exposing and Defending Backdoors in Pretrained Language Models
Peihai Jiang, Xixiang Lyu, Yige Li +1
Supervised fine-tuning has become the predominant method for adapting large pretrained models to downstream tasks. However, recent studies have revealed that these models are vulne…
Reconstructive Neuron Pruning for Backdoor Defense
Yige Li, Xixiang Lyu, Xingjun Ma +4
Deep neural networks (DNNs) have been found to be vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications. While existing…
Bulk carrier lifetime surpassing 600 us in Upgraded Metallurgical-grade Silicon multicrystalline wafers after Phosphorus Diffusion Gettering
Nerea Dasilva-Villanueva, Sergio Catalán-Gómez, David Fuertes Marrón +2
Upgraded metallurgical-grade (UMG) Si is obtained via a purification route alternative to the one used for conventional polysilicon and with significantly reduced environmental imp…
A Novel Variable K-Pseudonym Scheme Applied to 5G Anonymous Access Authentication
Dong Ma, Xixiang Lyu, Renpeng Zou
Anonymous access authentication schemes provide users with massive application services while protecting the privacy of users' identities. The identity protection schemes in 3G and…
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption
Jing Ma, Si-Ahmed Naas, Stephan Sigg +1
With the advance of machine learning and the internet of things (IoT), security and privacy have become key concerns in mobile services and networks. Transferring data to a central…
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
Yige Li, Xixiang Lyu, Nodens Koren +3
Deep neural networks (DNNs) are known vulnerable to backdoor attacks, a training time attack that injects a trigger pattern into a small proportion of training data so as to contro…
FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT
J. Li, L. Lyu, X. Liu +2
The distributed denial of service (DDoS) attack is detrimental to the industrial Internet of things (IIoT) as it triggers severe resource starvation on networked objects. Recent dy…