Hosted by CityU’s Center for Cybersecurity Innovation and School of Technology and Computing (STC), the Applied Research Symposium is open to faculty, professionals, and students from any discipline, university, or professional organization. At the end of each quarter, any students who would like to share their projects including capstone courses will present their outcomes. This symposium will provide opportunities for students, researchers, and practitioners to discuss the influence and impact of the applied computing on the future of our planet and our society
Description: This project looks at the current state of data mining and its uses in cyber forensics and looks ahead to the future to see what the possibilities are with AI and Block-chaining.
Description: “DeviceMaster” is a Master’s Capstone Project focused on solving the challenge of communicating with IoT devices behind firewalls. Utilizing edge computing principles, it introduces a website for cloud-based control of embedded devices, enhancing user experience with features like custom code deployment and result visualization. Leveraging technologies such as py4web and Vue.js, the project aims to provide a comprehensive platform for managing embedded devices efficiently. With key features including device registration and periodic synchronization, supported by a technology stack featuring Py4web, Vue.js, Bulma CSS, Celery, Redis, and SQLite, DeviceMaster promises fast and seamless device management and synchronization capabilities
Description: For my capstone project I’m doing an analysis of recall data from the NHTSA.
Description: This project proposes a system for enhancing team communication through multimodal sentiment analysis. By integrating advanced AI and machine learning technologies, including TensorFlow and spaCy, it analyzes video, audio, and text data to identify emotional cues and sentiment trends within team interactions. The system provides actionable insights via a user-friendly dashboard, offering tailored recommendations for improving collaboration dynamics, all while ensuring data privacy and security through robust encryption and ethical data handling practices.
Description: Using Python, NoSQL, and NLP, I’ll create a program to automatically add relevant skills to a resume based off the skills listed in a job description and a user’s skill database.
Description: Migrating EHRs to cloud computing brings in the influence of third parties who could directly compromise the privacy of data or introduce vulnerabilities that could be exploited by hackers to gain unauthorized access to the data. The failure to protect the privacy of EHRs in cloud amounts to a violation of the privacy requirements of HIPAA. The problem is the increased vulnerability of EHRs to privacy breaches due to migration to cloud computing.
Description: A brief oveview of how the pandemic shaped society and the economy, and how the job market has changed in response.
Description: Medicine time tracker app that will remind patients or users of the app to take medicine making patients more compliant. This application uses AI and ML algorithms to take pictures of handwritten prescriptions from doctors and make a schedule for medicine intake time and sets alarms.
Description: A local municipality relies on multiple sources of vulnerability data, including internal scans, CISA, and vendor reports, that exist in silos. This fragmentation of vulnerability information across disconnected systems reduces visibility into the true extent of risks and makes it challenging to prioritize remediation efforts. There is a need for a consolidated view of vulnerability findings to make data-driven risk management decisions. This project aims to develop an automated framework integrating vulnerability data from numerous feeds into a central system. The goals are to create a comprehensive, up-to-date inventory of cyber risks, enable effective prioritization and tracking of remediation activities, and implement dashboards or spreadsheets for improved visibility and reporting.
Description: The study demonstrated that the aviation industry is experiencing significant cybersecurity exposures and vulnerabilities, such as Ransomware attacks, Phishing, Distributed Denial of Service attacks, and Data breaches. We explored whether the aviation employment and deployment of targeted Artificial intelligence (AI) capabilities in the industry will positively improve the aviation industry’s cybersecurity posture and effectiveness. Analyzing cybersecurity use cases in other industries and demonstrating their transference to the aviation industry, we illustrate how AI can address cybersecurity risks and enable uninterrupted air travel.
|4:30 PM – 4:35 PM
Greeting & Announcement
Advisor: Dr. Sam Chung
Chair: Asia Shvets
Teams link: Main
|4:35 PM – 4:55 PM
Presenter 1: TBA
Teams link: Session 01
Presentation: 15 Minutes
Q&A: 5 minutes
|4:55 PM – 5:15 PM
Presenter 2: TBA
|5:15 PM – 5:35 PM
Presenter 3: TBA