1.5k citations · 5k across the 30 of their papers we have counts for
30 papers
Federated Learning for Cyber Physical Systems: A Comprehensive Survey
Minh K. Quan, Pubudu N. Pathirana, Mayuri Wijayasundara +5
The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliabili…
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data
Kanishka Ranaweera, Dinh C. Nguyen, Pubudu N. Pathirana +4
In the era of data-driven machine-learning applications, privacy concerns and the scarcity of labeled data have become paramount challenges. These challenges are particularly prono…
Federated Learning with Differential Privacy: An Utility-Enhanced Approach
Kanishka Ranaweera, Dinh C. Nguyen, Pubudu N. Pathirana +4
Federated learning has emerged as an attractive approach to protect data privacy by eliminating the need for sharing clients' data while reducing communication costs compared with…
Industrial Metaverse: Enabling Technologies, Open Problems, and Future Trends
Shiying Zhang, Jun Li, Long Shi +4
As an emerging technology that enables seamless integration between the physical and virtual worlds, the Metaverse has great potential to be deployed in the industrial production f…
Private Knowledge Sharing in Distributed Learning: A Survey
Yasas Supeksala, Dinh C. Nguyen, Ming Ding +5
The rise of Artificial Intelligence (AI) has revolutionized numerous industries and transformed the way society operates. Its widespread use has led to the distribution of AI and i…
HierSFL: Local Differential Privacy-aided Split Federated Learning in Mobile Edge Computing
Minh K. Quan, Dinh C. Nguyen, Van-Dinh Nguyen +3
Federated Learning is a promising approach for learning from user data while preserving data privacy. However, the high requirements of the model training process make it difficult…
Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems
Shiying Zhang, Jun Li, Long Shi +5
Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT). Nonetheles…
Holistic Survey of Privacy and Fairness in Machine Learning
Sina Shaham, Arash Hajisafi, Minh K Quan +6
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the…
Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework
Van-Dinh Nguyen, Thang X. Vu, Nhan Thanh Nguyen +6
To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open R…
Intelligent Blockchain-based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges
Dinh C. Nguyen, Van-Dinh Nguyen, Ming Ding +5
The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading wi…
Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing
Dinh C. Nguyen, Seyyedali Hosseinalipour, David J. Love +2
In this paper, we study a new latency optimization problem for blockchain-based federated learning (BFL) in multi-server edge computing. In this system model, distributed mobile de…
Federated Learning for Smart Healthcare: A Survey
Dinh C. Nguyen, Quoc-Viet Pham, Pubudu N. Pathirana +5
Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI techniques…
Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +2
COVID-19 has spread rapidly across the globe and become a deadly pandemic. Recently, many artificial intelligence-based approaches have been used for COVID-19 detection, but they o…
BEdgeHealth: A Decentralized Architecture for Edge-based IoMT Networks Using Blockchain
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding +1
The healthcare industry has witnessed significant transformations in e-health services by using mobile edge computing (MEC) and blockchain to facilitate healthcare operations. Many…
Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing with Multi-agent Deep Reinforcement Learning
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +3
The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in mobile networks, by offering task offloading solutions with security…
6G Internet of Things: A Comprehensive Survey
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +5
The sixth generation (6G) wireless communication networks are envisioned to revolutionize customer services and applications via the Internet of Things (IoT) towards a future of fu…
Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts
Quoc-Viet Pham, Dinh C. Nguyen, Thien Huynh-The +2
The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 214 countries and areas in the world, and ha…
Blockchain and AI-based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +1
The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 s…
Federated Learning for Industrial Internet of Things in Future Industries
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +4
The Industrial Internet of Things (IIoT) offers promising opportunities to transform the operation of industrial systems and becomes a key enabler for future industries. Recently,…
Toward Blockchain for Edge-of-Things: A New Paradigm, Opportunities, and Future Directions
Prabadevi B, N Deepa, Quoc-Viet Pham +5
Blockchain is gaining momentum as a promising technology for many application domains, one of them being the Edge-of- Things (EoT) that is enabled by the integration of edge comput…
Federated Learning for Internet of Things: A Comprehensive Survey
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +3
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI).…
Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
Dinh C. Nguyen, Ming Ding, Quoc-Viet Pham +6
Mobile edge computing (MEC) has been envisioned as a promising paradigm to handle the massive volume of data generated from ubiquitous mobile devices for enabling intelligent servi…
A Cooperative Architecture of Data Offloading and Sharing for Smart Healthcare with Blockchain
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding +1
The healthcare industry has witnessed significant transformations in e-health services where Electronic Health Records (EHRs) are transferred to mobile edge clouds to facilitate he…
A Survey on Blockchain for Big Data: Approaches, Opportunities, and Future Directions
Natarajan Deepa, Quoc-Viet Pham, Dinh C. Nguyen +6
Big data has generated strong interest in various scientific and engineering domains over the last few years. Despite many advantages and applications, there are many challenges in…