Recent success of deep learning is largely attributed to the sheer amount of data used for
training deep neural networks. Despite the unprecedented success, the massive data …

Together with impressive advances touching every aspect of our society, AI technology
based on Deep Neural Networks (DNN) is bringing increasing security concerns. While …

Voice Recognition Systems (VRSs) employ deep learning for speech recognition and
speaker recognition. They have been widely deployed in various real-world applications …

Abstract We present a Multimodal Backdoor defense technique TIJO (Trigger Inversion
using Joint Optimization). Recently Walmer et al. demonstrated successful backdoor attacks …

Dataset distillation has emerged as a prominent technique to improve data efficiency when
training machine learning models. It encapsulates the knowledge from a large dataset into a …

Resource management, security, and privacy stand as fundamental pillars for the reliable
and secure operation of efficient semantic communications (SC) system. By addressing …

Image recognition is one of the important branches of computer vision, which has important
theoretical and practical significance. For the insufficient use of features, the single type of …

The log messages generated in the system reflect the state of the system at all times. The
realization of autonomous detection of abnormalities in log messages can help operators …

Convolutional neural networks (CNNs) have been prominent in most hyperspectral image
(HSI) processing applications due to their advantages in extracting local information …

Establishing how a set of learners can provide privacy-preserving federated learning in a
fully decentralized (peer-to-peer, no coordinator) manner is an open problem. We propose …