Search Results for author: Kwok-Yan Lam

Found 13 papers, 2 papers with code

New Threats against Object Detector with Non-local Block

no code implementations ECCV 2020 Yi Huang, Fan Wang, Adams Wai-Kin Kong, Kwok-Yan Lam

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

1 code implementation8 May 2022 Zhi Li, Rizhao Cai, Haoliang Li, Kwok-Yan Lam, Yongjian Hu, Alex C. Kot

Under this framework, a teacher network is trained with source domain samples to provide discriminative feature representations for face PAD.

Face Presentation Attack Detection

Asymmetric Modality Translation For Face Presentation Attack Detection

no code implementations18 Oct 2021 Zhi Li, Haoliang Li, Xin Luo, Yongjian Hu, Kwok-Yan Lam, Alex C. Kot

In this paper, we propose a novel framework based on asymmetric modality translation for face presentation attack detection in bi-modality scenarios.

Face Presentation Attack Detection Face Recognition +1

Spectrum Sharing for 6G Integrated Satellite-Terrestrial Communication Networks Based on NOMA and Cognitive Radio

no code implementations27 Jan 2021 Xin Liu, Kwok-Yan Lam, Feng Li, Jun Zhao, Li Wang

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

no code implementations4 Jan 2021 Jenn-Bing Ong, Wee-Keong Ng, Ivan Tjuawinata, Chao Li, Jielin Yang, Sai None Myne, Huaxiong Wang, Kwok-Yan Lam, C. -C. Jay Kuo

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.

Dimensionality Reduction Tensor Networks

A Comprehensive Survey of 6G Wireless Communications

no code implementations21 Dec 2020 Yang Zhao, Wenchao Zhai, Jun Zhao, Tinghao Zhang, Sumei Sun, Dusit Niyato, Kwok-Yan Lam

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

no code implementations28 Nov 2020 Helin Yang, Jun Zhao, Zehui Xiong, Kwok-Yan Lam, Sumei Sun, Liang Xiao

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.

Distributed Computing Federated Learning

Secure Weighted Aggregation for Federated Learning

no code implementations17 Oct 2020 Jiale Guo, Ziyao Liu, Kwok-Yan Lam, Jun Zhao, Yiqiang Chen, Chaoping Xing

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

no code implementations9 Aug 2020 Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, Kwok-Yan Lam

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

no code implementations24 Jul 2020 Ziyao Liu, Ivan Tjuawinata, Chaoping Xing, Kwok-Yan Lam

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

no code implementations19 Apr 2020 Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam

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.

Federated Learning

Reviewing and Improving the Gaussian Mechanism for Differential Privacy

no code implementations27 Nov 2019 Jun Zhao, Teng Wang, Tao Bai, Kwok-Yan Lam, Zhiying Xu, Shuyu Shi, Xuebin Ren, Xinyu Yang, Yang Liu, Han Yu

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

1 code implementation8 Nov 2019 Muhammad Baqer Mollah, Jun Zhao, Dusit Niyato, Kwok-Yan Lam, Xin Zhang, Amer M. Y. M. Ghias, Leong Hai Koh, Lei Yang

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

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