Search Results for author:
Found 13 papers, 2 papers with code
New Threats against Object Detector with Non-local Block
The experiments show that the universal patches are able to mislead the detector with greater probabilities.
One-Class Knowledge Distillation for Face Presentation Attack Detection
Under this framework, a teacher network is trained with source domain samples to provide discriminative feature representations for face PAD.
Asymmetric Modality Translation For Face Presentation Attack Detection
In this paper, we propose a novel framework based on asymmetric modality translation for face presentation attack detection in bi-modality scenarios.
Spectrum Sharing for 6G Integrated Satellite-Terrestrial Communication Networks Based on NOMA and Cognitive Radio
ISTCN aims to provide high speed and pervasive network services by integrating broadband terrestrial mobile networks with satellite communication networks.
Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation
The distributed tensor representations are dispersed on multiple clouds / fogs or servers / devices with metadata privacy, this provides both distributed trust and management to seamlessly secure big data storage, communication, sharing, and computation.
A Comprehensive Survey of 6G Wireless Communications
First, we give an overview of 6G from perspectives of technologies, security and privacy, and applications.
Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management
However, due to the privacy concerns of devices and limited computation or communication resource of UAVs, it is impractical to send raw data of devices to UAV servers for model training.
Secure Weighted Aggregation for Federated Learning
The situation is exacerbated by the cloud-based implementation of digital services when user data are captured and stored in distributed locations, hence aggregation of the user data for ML could be a serious breach of privacy regulations.
Cryptography and Security Distributed, Parallel, and Cluster Computing
Local Differential Privacy and Its Applications: A Comprehensive Survey
Local differential privacy (LDP), as a strong privacy tool, has been widely deployed in the real world in recent years.
Cryptography and Security
MPC-enabled Privacy-Preserving Neural Network Training against Malicious Attack
The application of secure multiparty computation (MPC) in machine learning, especially privacy-preserving neural network training, has attracted tremendous attention from the research community in recent years.
Local Differential Privacy based Federated Learning for Internet of Things
To avoid the privacy threat and reduce the communication cost, in this paper, we propose to integrate federated learning and local differential privacy (LDP) to facilitate the crowdsourcing applications to achieve the machine learning model.
Reviewing and Improving the Gaussian Mechanism for Differential Privacy
Although both classical Gaussian mechanisms [1, 2] assume $0 < \epsilon \leq 1$, our review finds that many studies in the literature have used the classical Gaussian mechanisms under values of $\epsilon$ and $\delta$ where the added noise amounts of [1, 2] do not achieve $(\epsilon,\delta)$-DP.
Blockchain for Future Smart Grid: A Comprehensive Survey
In this paper, we aim to provide a comprehensive survey on application of blockchain in smart grid.
Cryptography and Security Distributed, Parallel, and Cluster Computing Networking and Internet Architecture Social and Information Networks Systems and Control Systems and Control
