1.5k citations · 5.4k across the 33 of their papers we have counts for
33 papers
SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks
Omid Tavallaie, Kanchana Thilakarathna, Suranga Seneviratne +2
Federated Learning (FL) is a distributed machine learning paradigm designed for privacy-sensitive applications that run on resource-constrained devices with non-Identically and Ind…
Detecting and Characterising Mobile App Metamorphosis in Google Play Store
D. Denipitiyage, B. Silva, K. Gunathilaka +4
App markets have evolved into highly competitive and dynamic environments for developers. While the traditional app life cycle involves incremental updates for feature enhancements…
Usability of Privacy Controls in Top Health Websites
Ravin Gunawardena, Yuemeng Yin, Yi Huang +5
With the increasing awareness and concerns around privacy, many service providers offer their users various privacy controls. Through these controls, users gain greater authority o…
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…
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…