Completed Projects
Completed research funding, grants, and collaborative projects at the IIS Laboratory.
Secure and Efficient Federated Learning for Automated Internet-of-Things Environment
This project aims to perform comprehensive research on Federated Learning algorithms (FL) to enhance both security and efficiency. FL is a new framework that data is distributed over millions of mobile devices, Edge computing hosts, and servers. Instead of collecting everyone's dataset at a central server, FL trains data on each device and does not transfer a training result as a form of parameters or gradients to the server. Then the server will be able to obtain the final training model by averaging the results from participating devices.
The major advantage of FL is that it provides highly personalized models and does not compromise user privacy. However, some recent research indicates that the following vulnerabilities of FL can be exploited to negate the key advantages, such as:
- Model Inversion Attack
- Membership Inference Attack
- Model Extraction Attack
This project will focus on enhancing security and efficiency of FL algorithms. Specifically, this project has the following objectives:
- (a) Discovering hidden weaknesses or potential vulnerabilities of FL
- (b) Developing new FL algorithms, architectures, or computing models that are secure against those attacks
- (c) Establishing simulation environments to evaluate the proposed scheme
- (d) Demonstrating the effectiveness of the proposed scheme
A Federated Approach to Image Feature Extraction
Collaborators:
- Mingon Kang, University of Nevada, Las Vegas, http://mkang.faculty.unlv.edu/
- Reza Parizi, Kennesaw State University, http://facultyweb.kennesaw.edu/rparizi1/index.php
Research on ICT Core Technologies and Cultivation of Innovative Talents to Lead Next-Generation Smart Healthcare
The aim of this research project is to develop core technologies for next-generation smart healthcare environment. Specifically, the following sub-project will be performed:
- (a) Development of a new blockchain suitable for Internet of Things and body sensor networks
- (b) Development of privacy-preserving data management schemes including Fintech and security and privacy solutions for Fog/Edge based cloud computing environment
- (c) Development of survival analysis involving artificial intelligent (AI) and deep learning algorithms