Trusted ai in multiagent systems: An overview of privacy and security for distributed learning

C Ma, J Li, K Wei, B Liu, M Ding, L Yuan… - Proceedings of the …, 2023‏ - ieeexplore.ieee.org
Motivated by the advancing computational capacity of distributed end-user equipment (UE),
as well as the increasing concerns about sharing private data, there has been considerable …

Enabling and emerging technologies for social distancing: a comprehensive survey and open problems

CT Nguyen, YM Saputra, N Van Huynh… - arxiv preprint arxiv …, 2020‏ - arxiv.org
Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses
such as COVID-19. By minimizing the close physical contact among people, we can reduce …

User-level privacy-preserving federated learning: Analysis and performance optimization

K Wei, J Li, M Ding, C Ma, H Su… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Federated learning (FL), as a type of collaborative machine learning framework, is capable
of preserving private data from mobile terminals (MTs) while training the data into useful …

Blockchain assisted decentralized federated learning (BLADE-FL): Performance analysis and resource allocation

J Li, Y Shao, K Wei, M Ding, C Ma, L Shi… - … on Parallel and …, 2021‏ - ieeexplore.ieee.org
Federated learning (FL), as a distributed machine learning paradigm, promotes personal
privacy by local data processing at each client. However, relying on a centralized server for …

Low-latency federated learning over wireless channels with differential privacy

K Wei, J Li, C Ma, M Ding, C Chen, S **… - IEEE Journal on …, 2021‏ - ieeexplore.ieee.org
In federated learning (FL), model training is distributed over clients and local models are
aggregated by a central server. The performance of uploaded models in such situations can …

A triple real-time trajectory privacy protection mechanism based on edge computing and blockchain in mobile crowdsourcing

W Wang, Y Wang, P Duan, T Liu… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
With the rapid development of the Internet of Things (IoT) and the rapid popularization of 5 G
networks, the data that needs to be processed in Mobile Crowdsourcing (MCS) system is …

A comprehensive survey of enabling and emerging technologies for social distancing—Part II: Emerging technologies and open issues

CT Nguyen, YM Saputra, N Van Huynh… - Ieee …, 2020‏ - ieeexplore.ieee.org
This two-part paper aims to provide a comprehensive survey on how emerging
technologies, eg, wireless and networking, artificial intelligence (AI) can enable, encourage …

Privacy protection federated learning system based on blockchain and edge computing in mobile crowdsourcing

W Wang, Y Wang, Y Huang, C Mu, Z Sun, X Tong… - Computer …, 2022‏ - Elsevier
With the rapid popularization and development of the Internet of Things (IoT) and 5G
networks, mobile crowdsourcing (MCS) has become an indispensable part in today's …

A novel exploitative and explorative GWO-SVM algorithm for smart emotion recognition

X Yan, Z Lin, Z Lin, B Vucetic - IEEE Internet of Things Journal, 2023‏ - ieeexplore.ieee.org
Emotion recognition or detection is broadly utilized in patient–doctor interactions for
diseases, such as schizophrenia and autism and the most typical techniques are speech …

When AI meets information privacy: The adversarial role of AI in data sharing scenario

A Majeed, SO Hwang - IEEE Access, 2023‏ - ieeexplore.ieee.org
Artificial intelligence (AI) is a transformative technology with a substantial number of practical
applications in commercial sectors such as healthcare, finance, aviation, and smart cities. AI …