569 citations · 863 across the 13 of their papers we have counts for
13 papers
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey
Yichen Wan, Youyang Qu, Wei Ni +3
Due to the greatly improved capabilities of devices, massive data, and increasing concern about data privacy, Federated Learning (FL) has been increasingly considered for applicati…
From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding
Borui Cai, Yong Xiang, Longxiang Gao +4
Knowledge graph embedding (KGE) that maps entities and relations into vector representations is essential for downstream applications. Conventional KGE methods require high-dimensi…
A Comprehensive Survey on Edge Data Integrity Verification: Fundamentals and Future Trends
Yao Zhao, Youyang Qu, Yong Xiang +3
Recent advances in edge computing~(EC) have pushed cloud-based data caching services to edge, however, such emerging edge storage comes with numerous challenging and unique securit…
An Efficient and Reliable Asynchronous Federated Learning Scheme for Smart Public Transportation
Chenhao Xu, Youyang Qu, Tom H. Luan +3
Since the traffic conditions change over time, machine learning models that predict traffic flows must be updated continuously and efficiently in smart public transportation. Feder…
Temporal Knowledge Graph Completion: A Survey
Borui Cai, Yong Xiang, Longxiang Gao +3
Knowledge graph completion (KGC) can predict missing links and is crucial for real-world knowledge graphs, which widely suffer from incompleteness. KGC methods assume a knowledge g…
Semantic Code Search for Smart Contracts
Chaochen Shi, Yong Xiang, Jiangshan Yu +1
Semantic code search technology allows searching for existing code snippets through natural language, which can greatly improve programming efficiency. Smart contracts, programs th…
Asynchronous Federated Learning on Heterogeneous Devices: A Survey
Chenhao Xu, Youyang Qu, Yong Xiang +1
Federated learning (FL) is a kind of distributed machine learning framework, where the global model is generated on the centralized aggregation server based on the parameters of lo…
Prototype-Guided Memory Replay for Continual Learning
Stella Ho, Ming Liu, Lan Du +2
Continual learning (CL) refers to a machine learning paradigm that learns continuously without forgetting previously acquired knowledge. Thereby, major difficulty in CL is catastro…
Low-level Comments auto-generation for Solidity Smart Contracts
Chaochen Shi, Yong Xiang, Jiangshan Yu +2
Context: Decentralized applications on blockchain platforms are realized through smart contracts. However, participants who lack programming knowledge often have difficulties readi…
A Bytecode-based Approach for Smart Contract Classification
Chaochen Shi, Yong Xiang, Robin Ram Mohan Doss +3
With the development of blockchain technologies, the number of smart contracts deployed on blockchain platforms is growing exponentially, which makes it difficult for users to find…
SCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems
Chenhao Xu, Jiaqi Ge, Yong Li +5
Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy. FL is effective when dealing with independent and identical…
Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data
R G Gayathri, Atul Sajjanhar, Yong Xiang +1
Insider threats are the cyber attacks from within the trusted entities of an organization. Lack of real-world data and issue of data imbalance leave insider threat analysis an unde…
Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions
Ranesh Kumar Naha, Saurabh Garg, Dimitrios Georgakopoulos +4
Emerging technologies like the Internet of Things (IoT) require latency-aware computation for real-time application processing. In IoT environments, connected things generate a hug…