709 citations · 2.4k across the 11 of their papers we have counts for
11 papers
Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Yi Liu, Ruihui Zhao, Jiawen Kang +3
Federated Edge Learning (FEL) allows edge nodes to train a global deep learning model collaboratively for edge computing in the Industrial Internet of Things (IIoT), which signific…
Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks and Defenses
Yi Liu, Xingliang Yuan, Ruihui Zhao +3
Semi-supervised Federated Learning (SSFL) has recently drawn much attention due to its practical consideration, i.e., the clients may only have unlabeled data. In practice, these S…
Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework
Jiawen Kang, Zehui Xiong, Chunxiao Jiang +6
The emerging Federated Edge Learning (FEL) technique has drawn considerable attention, which not only ensures good machine learning performance but also solves "data island" proble…
Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms
Yi Liu, Jiangtian Nie, Xuandi Li +3
Due to air quality significantly affects human health, it is becoming increasingly important to accurately and timely predict the Air Quality Index (AQI). To this end, this paper p…
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach
Yi Liu, Sahil Garg, Jiangtian Nie +4
Since edge device failures (i.e., anomalies) seriously affect the production of industrial products in Industrial IoT (IIoT), accurately and timely detecting anomalies is becoming…
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Yi Liu, Xingliang Yuan, Zehui Xiong +3
As the 5G communication networks are being widely deployed worldwide, both industry and academia have started to move beyond 5G and explore 6G communications. It is generally belie…
A Secure Federated Learning Framework for 5G Networks
Yi Liu, Jialiang Peng, Jiawen Kang +3
Federated Learning (FL) has been recently proposed as an emerging paradigm to build machine learning models using distributed training datasets that are locally stored and maintain…
Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach
Yi Liu, James J. Q. Yu, Jiawen Kang +2
Existing traffic flow forecasting approaches by deep learning models achieve excellent success based on a large volume of datasets gathered by governments and organizations. Howeve…
PPGAN: Privacy-preserving Generative Adversarial Network
Yi Liu, Jialiang Peng, James J. Q Yu +1
Generative Adversarial Network (GAN) and its variants serve as a perfect representation of the data generation model, providing researchers with a large amount of high-quality gene…
Dominant Dataset Selection Algorithms for Electricity Consumption Time-Series Data Analysis Based on Affine Transformation
Yi Wu, Yi Liu, Syed Hassan Ahmed +2
The explosive growth of time-series data, the scale of time-series data (TSD) suggests that the scale and capability of many Internet of Things (IoT)-based applications has already…
Big Data Platform Architecture Under The Background of Financial Technology
Yi Liu, Jiawen Peng, Zhihao Yu
With the rise of the concept of financial technology, financial and technology gradually in-depth integration, scientific and technological means to become financial product innova…