Through continuous research and sound development practices, we aim to implement a lightweight, privacy-preserving algorithm that protects data in AI applications in IoT-cloud environments against emerging security threats. AI and IoT are transforming industries by making devices smarter, more connected, and efficient, but the increased connectivity creates security challenges. IoT devices often lack the resources for traditional security measures. Therefore, this creates the need for lightweight solutions that protect data without compromising performance.
Study Use of AR-VR in Gaming Scenario
The goal of our project is to see how AR and VR, specifically using the Oculus Quest 2, can make gaming more immersive and interactive. We’re building a system that collects sensor data from players while they’re using the headset, like where they’re looking and how they’re moving. After gathering that data, we’ll create a tool to replay and visualize the experience so someone else can watch it later. At the end, we’ll put everything together in a paper that walks through what we built, how we did it, and what we learned along the way.
Synesthesia AR Experience
To leverage Augmented Reality (AR) to simulate audio-visual synesthesia; the neurological phenomenon where auditory stimuli trigger automatic visual perceptions. This project should enable non-synesthetic users to conceptualize, comprehend, and appreciate the unique way in which music is perceived by synesthetes.
Deep Fake Detection
To develop a robust and intuitive interface that applies the top-performing deepfake detection method to support digital media authenticity and reduce the spread of misinformation.
Empirical Analysis of Differential Privacy
To provide actionable insights into how to optimize differential privacy implementations for various practical applications, ensuring a strong balance between security and data usefulness.
CTF 2.0
VISION To establish a dynamic platform that encourages exploration, innovation, and collaboration in the field of cybersecurity. Our vision is to empower individuals and teams to continuously enhance their skills, adapt to emerging challenges, and contribute to a safer digital landscape. MISSION To create and orchestrate a Capture the Flag (CTF) event, challenging participants with […]
AR Project
Our team is creating software that will interact with hardware, benefiting people that can use accessibility features. This software will enable users wearing Meta Quest to virtually open and close doors with ease, making the process more accessible for those in need.
Automatic Composition
CLIENT Chi-Hao Cheng, ECE TEAM Longze Li (CSE), Daniel Wood (ECE)
Computer Vision For HealthCare
Research and create an application that combines computer vision and machine learning to allow users to quickly identify dental issues.
Security of Machine Learning II
Integrate model extraction attacks with membership inference techniques to enhance the efficacy of membership inference.