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.
no code implementations • 31 Mar 2024 • Jingyu Wang, Niantai Jing, Ziyao Liu, Jie Nie, Yuxin Qi, Chi-Hung Chi, Kwok-Yan Lam
Additionally, we extract inconsistent regions between coarse similar regions obtained through self-correlation calculations and regions composed of prototypes.
no code implementations • 30 Mar 2024 • Renyang Liu, Kwok-Yan Lam, Wei Zhou, Sixing Wu, Jun Zhao, Dongting Hu, Mingming Gong
Many attack techniques have been proposed to explore the vulnerability of DNNs and further help to improve their robustness.
no code implementations • 29 Mar 2024 • Jiani Fan, Minrui Xu, Ziyao Liu, Huanyi Ye, Chaojie Gu, Dusit Niyato, Kwok-Yan Lam
Artificial Intelligence-Generated Content (AIGC) refers to the paradigm of automated content generation utilizing AI models.
no code implementations • 20 Mar 2024 • Ziyao Liu, Huanyi Ye, Chen Chen, Kwok-Yan Lam
Machine Unlearning (MU) has gained considerable attention recently for its potential to achieve Safe AI by removing the influence of specific data from trained machine learning models.
no code implementations • 4 Feb 2024 • Tinghao Zhang, Kwok-Yan Lam, Jun Zhao
For scalability, practical HFL schemes select a subset of IoT devices to participate in the training, hence the notion of device scheduling.
no code implementations • 16 Jan 2024 • Yu Jiang, Jiyuan Shen, Ziyao Liu, Chee Wei Tan, Kwok-Yan Lam
Federated learning (FL) is vulnerable to poisoning attacks, where malicious clients manipulate their updates to affect the global model.
no code implementations • 12 Dec 2023 • Renyang Liu, Wei Zhou, Sixin Wu, Jun Zhao, Kwok-Yan Lam
Extensive studies have demonstrated that deep neural networks (DNNs) are vulnerable to adversarial attacks, which brings a huge security risk to the further application of DNNs, especially for the AI models developed in the real world.
no code implementations • 26 Oct 2023 • Terence Jie Chua, Wenhan Yu, Jun Zhao, Kwok-Yan Lam
FedPEAT uses adapters, emulators, and PEFT for federated model tuning, enhancing model privacy and memory efficiency.
1 code implementation • 16 Oct 2023 • Jiyuan Shen, Wenzhuo Yang, Kwok-Yan Lam
We observed that the smoothness of expert trajectories has a significant impact on subsequent student parameter alignment.
no code implementations • 15 Oct 2023 • Renyang Liu, Jinhong Zhang, Kwok-Yan Lam, Jun Zhao, Wei Zhou
However, the distribution of these fake data lacks diversity and cannot detect the decision boundary of the target model well, resulting in the dissatisfactory simulation effect.
no code implementations • 11 Oct 2023 • Renyang Liu, Wei Zhou, Tianwei Zhang, Kangjie Chen, Jun Zhao, Kwok-Yan Lam
Existing black-box attacks have demonstrated promising potential in creating adversarial examples (AE) to deceive deep learning models.
no code implementations • 17 Sep 2023 • Tinghao Zhang, Kwok-Yan Lam, Jun Zhao
The large population of wireless users is a key driver of data-crowdsourced Machine Learning (ML).
no code implementations • 18 Aug 2023 • Peiyuan Si, Jun Zhao, Kwok-Yan Lam, Qing Yang
In this paper, we aim to explore the use of uplink semantic communications with the assistance of UAV in order to improve data collection effiicency for metaverse users in remote areas.
no code implementations • 11 Jul 2023 • Chen Chen, YuFei Wang, Yang Zhang, Quan Z. Sheng, Kwok-Yan Lam
Previous KGC methods typically represent knowledge graph entities and relations as trainable continuous embeddings and fuse the embeddings of the entity $h$ (or $t$) and relation $r$ into hidden representations of query $(h, r, ?
2 code implementations • 4 Jul 2023 • Chen Chen, YuFei Wang, Aixin Sun, Bing Li, Kwok-Yan Lam
However, the fine-tuned PLMs often overwhelmingly focus on the textual information and overlook structural knowledge.
no code implementations • 29 May 2023 • Peiyuan Si, Liangxin Qian, Jun Zhao, Kwok-Yan Lam
Unmanned aerial vehicles (UAVs) are promising for providing communication services due to their advantages in cost and mobility, especially in the context of the emerging Metaverse and Internet of Things (IoT).
no code implementations • 4 Jan 2023 • Peiyuan Si, Wenhan Yu, Jun Zhao, Kwok-Yan Lam, Qing Yang
A huge amount of data in physical world needs to be synchronized to the virtual world to provide immersive experience for users, and there will be higher requirements on coverage to include more users into Metaverse.
no code implementations • 20 Nov 2022 • Ruohan Meng, Zhili Zhou, Qi Cui, Kwok-Yan Lam, Alex Kot
Extensive experiments, on diverse datasets and unseen manipulations, demonstrate that the proposed tagging approach achieves excellent performance in the aspects of both authenticity verification and source tracing for reliable fake news detection and outperforms the prior works.
no code implementations • 11 Oct 2022 • Tinghao Zhang, Zhijun Li, Yongrui Chen, Kwok-Yan Lam, Jun Zhao
A reinforcement learning (RL)-based DNN compression approach is used to generate the lightweight model suitable for the edge from the heavyweight model.
1 code implementation • 29 Sep 2022 • Qiao Han, Jun Zhao, Kwok-Yan Lam
This research aims to make metaverse characters more realistic by adding lip animations learnt from videos in the wild.
no code implementations • 28 Sep 2022 • Peiyuan Si, Jun Zhao, Huimei Han, Kwok-Yan Lam, Yang Liu
With the development of blockchain and communication techniques, the Metaverse is considered as a promising next-generation Internet paradigm, which enables the connection between reality and the virtual world.
1 code implementation • COLING 2022 • Chen Chen, YuFei Wang, Bing Li, Kwok-Yan Lam
To remedy the KG structure information loss from the "flat" text, we further improve the input representations of entities and relations, and the inference algorithm in KG-S2S.
1 code implementation • 8 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.
no code implementations • 18 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.
no code implementations • 27 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.
no code implementations • 4 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.
no code implementations • 21 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.
no code implementations • 28 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.
no code implementations • 17 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
no code implementations • 9 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
no code implementations • 24 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.
no code implementations • 19 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.
no code implementations • 27 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.
1 code implementation • 8 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