Chúc mừng các nhóm sinh viên nhóm nghiên cứu UiTiOt Khoa MMT&TT đã có bài báo được chấp nhận tại Hội nghị quốc tế ComNetSat 2024 được tổ chức tại Lombok, Indonesia.
Bài báo 1: A Home Health Monitoring System Based on Federated Learning and Blockchain Technology
– Sinh viên thực hiện:
+ Huỳnh Phi Long – MMCL 2020 – Tác giả chính
+ Nguyễn Xuân Dương – MMCL 2020 – Đồng tác giả
– Giảng viên hướng dẫn: PGS. TS. Lê Trung Quân, ThS. Nguyễn Khánh Thuật và ThS. Trần Thị Dung
– Tóm tắt: As society advances, healthcare has become essential for everyone. New technology is needed to improve healthcare and keep up with changing medical needs. This paper proposes a new home health monitoring system that uses a special blockchain system with a learning technique called Federated Learning. This means people can be monitored at home instead of going to hospitals. The system uses special computer programs (Deep Learning Neural Network and Convolutional Neural Network) to analyze health data and predict diseases like diabetes and pneumonia with an accuracy of approximately 90%. Federated Learning keeps user data secure by sharing only a small part of the data with other hospitals. The system also uses blockchain technology, like a secure lockbox, to further protect data and prevent theft during communication between hospitals. Accurate disease prediction offers significant benefits, including early detection, timely intervention, and better management of chronic conditions, ultimately improving patient outcomes and reducing the burden on healthcare facilities. This new system not only enhances access to healthcare at home but also keeps data safe and private.
Bài báo 2: A Network-Based Intrusion Detection System for Internet of Things on Swarm Learning
– Thực hiện:
+ Thầy Văn Thiên Luân – Tác giả chính
+ Vũ Minh Đức – ATTT 2020 – Đồng tác giả
+ Dương Trần Trà My – ATTT 2020 – Đồng tác giả
+ Phạm Nguyễn Hải Anh – ANTN 2021 – Đồng tác giả
+ Nguyễn Đàm Nhật Anh – MMTT 2020 – Đồng tác giả
– Giảng viên hướng dẫn: PGS. TS. Lê Trung Quân và ThS. Nguyễn Khánh Thuật
– Tóm tắt: In recent years, IoT applications have become increasingly popular. Smart services have been deployed from the IoT infrastructure to provide convenience for humans in their lives and related activities. Alongside IoT’s potential, security and privacy concerns have been highlighted in the IoT architecture. One weakness of the IoT system is the widespread deployment of sensor nodes with wireless connections. Additionally, the limited resources of these sensor nodes pose a challenge in designing and implementing security solutions for the IoT infrastructure. In this article, we plan to deploy a Network Intrusion Detection System (NIDS) for IoT infrastructure. This system is designed to run on the Swarm Learning framework, which supports decentralized machine learning models to ensure data distribution during training. This framework also operates on Ethereum – an open-source blockchain platform – to ensure authenticity and security while training decentralized machine learning models. We experiment with various scenarios using the CNN model via the CICIoT2023 dataset. The results demonstrate that our proposed system ensures accuracy comparable to centralized machine learning and Federated Learning models. We also experiment and evaluate the merge methods of decentralized machine learning models. Even though the mean method achieves the best performance, the coordmedian and geomedian methods give greater accuracy in results.
Homepage Hội nghị: https://comnetsat.org/
Thông tin Hội nghị: The forthcoming IEEE International Conference on Communications, Networks, and Satellite (COMNETSAT) 2024 will be held in Mataram, Lombok, Indonesia, on November 28–30, with a hybrid system (online and offline). IEEE COMNETSAT is a prestigious venue for academics and professionals from all over the world to exchange ideas and present the outcomes of ongoing research in the most cutting-edge areas of communications, network and information technology, satellite, broadband and photonics, data science, and artificial intelligence. We hope that the 13th IEEE COMNETSAT may build on the success of the previous IEEE COMNETSAT conferences and develop into a notable and prevalent conference year after year with the help of the IEEE Communications Society.
