7 papers
PoiCGAN: A Targeted Poisoning Based on Feature-Label Joint Perturbation in Federated Learning
Tao Liu, Jiguang Lv, Dapeng Man +7
Federated Learning (FL), as a popular distributed learning paradigm, has shown outstanding performance in improving computational efficiency and protecting data privacy, and is wid…
From Human Speech to Ocean Signals: Transferring Speech Large Models for Underwater Acoustic Target Recognition
Mengcheng Huang, Xue Zhou, Chen Xu +1
Underwater acoustic target recognition (UATR) plays a vital role in marine applications but remains challenging due to limited labeled data and the complexity of ocean environments…
Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning
Xue Zhou, Dapeng Man, Chen Xu +6
Offline reinforcement learning (RL) heavily relies on the coverage of pre-collected data over the target policy's distribution. Existing studies aim to improve data-policy coverage…
Act in Collusion: Distributed Multi-Target Backdoor Attacks in Federated Learning
Tao Liu, Dapeng Man, Jiguang Lv +6
Federated learning (FL) is widely used in Internet-of-Things (IoT) systems, but its distributed training process also exposes it to backdoor attacks. Existing studies mainly consid…
Revisiting Interpolation Augmentation for Speech-to-Text Generation
Chen Xu, Jie Wang, Xiaoqian Liu +6
Speech-to-text (S2T) generation systems frequently face challenges in low-resource scenarios, primarily due to the lack of extensive labeled datasets. One emerging solution is cons…
Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning
Tao Liu, Yuhang Zhang, Zhu Feng +4
Backdoors on federated learning will be diluted by subsequent benign updates. This is reflected in the significant reduction of attack success rate as iterations increase, ultimate…
Bridging the Gaps of Both Modality and Language: Synchronous Bilingual CTC for Speech Translation and Speech Recognition
Chen Xu, Xiaoqian Liu, Erfeng He +6
In this study, we present synchronous bilingual Connectionist Temporal Classification (CTC), an innovative framework that leverages dual CTC to bridge the gaps of both modality and…