Secure and Efficient Federate Learning for Automated Internet-of-Things Environment

Sponsor: Institute of Information & Communications Technology Planning & Evaluation (IITP), South Korea
Budget: KRW₩ 120,000,000 ($102,358.39)
Period: May 1, 2021 - October 31, 2022

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 enormous datasets at a central server, FL trains data on each device and 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 results introduced the following vulnerabilities of FL which can be exploited to negate the key advantages, such as (a) Model Inversion Attack, (b) Membership Inference Attack, (c) Model Extraction Attack, etc.
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

Sponsor: Oracle
Budget: US$200,000
Period: June 1, 2019 - May 31, 2021

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

Sponsor: Institute of Information & Communications Technology Planning & Evaluation (IITP), South Korea
Budget: KRW₩ 950,000,000 (Approx. US$800,000) with KSU portion of US$199,737.92 + stipend for 5 visiting graduate students
Period: July 1, 2019 - June 30, 2021

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.