This project is a GDPR Data Noncompliance Detector, developed as part of the COS 301 Capstone Project.
The GDPR Data Noncompliance Detector is a software tool designed to identify instances of noncompliance with the General Data Protection Regulation (GDPR). It analyzes data sets and identifies potential violations of GDPR principles, such as unauthorized data processing, inadequate security measures, or lack of consent.
GND.aprilfour.mp4
Download GND -> đź“Ą
Step 1: Click on the link to download the GND application Installer.
Step 2: Follow the instructions in the installation wizard to install the application on your computer.
Step 3: After the application is installed, you will need to restart your computer.
Step 4: After your computer has restarted, you will receive a notification, indicating that the GND server has started and you will be able to use the application.
Demo 2 SRS Documentation
Demo 2 Video Presentation
Demo 2 Presentation
Demo 2 Help Document
Demo 3 SRS Documentation
Demo 3 Video Presentation
Demo 4 SRS Documentation
Demo 4 Testing Specification
Architectural Document
Architectural Diagram
GitHub Issues and GitHub Boards
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Role: Team Leader/Backend Engineer
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Dhinaz is currently pursuing Computer Science, Statistics, and Data Science. He has worked with multiple technologies relating to all fields and is especially interested in AI, ML, and regression applications. He has completed multiple design and research projects related to data analysis and software modeling, two of which are linked above. He is also self-taught in Tableau and is currently working as a teaching assistant for COS 221 (Introduction to databases) at the University of Pretoria. |
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Role: Designer/Frontend Engineer
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As a third-year BSc Information and Knowledge Systems student, I specialize in merging technology and business insights to craft captivating social media web apps. Proficient in front-end development technologies like React, Ionic, and Angular, I implement innovative solutions efficiently. My passion for design enhances user experiences, reflecting in my projects where I prioritize intuitive interfaces and engaging interactions. A natural team player, I excel in collaborative environments, leading and contributing with determination and an open mind. Continuously refining my skills in front-end development, I am poised to make a significant impact in technology and enterprise. |
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Role: Backend Engineer/DevOps
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I am a final year BSc Information and Knowledge Systems student. This degree has allowed me to gain invaluable experience in not only the fields of computer science but also statistics and data analytics. I have a vested interest in the field of data science and using the insights that can be gained from analyzing a system to optimize it as much as possible. I have experience in building comprehensive web and desktop applications and have worked on the frontend side of development for multiple projects. |
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Role: Backend Developer/DevOps
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I am a final year Computer Science student at the University of Pretoria. My degree has exposed me to many computer science concepts. In web development, I enjoy backend and API development. I also enjoy learning about the field of graphics programming. I have a keen interest in machine learning and AI. With my knowledge, I aim to aid my team with the skills I have learnt in graphics and data visualization. |
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Role: Full Stack Developer
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I am a final year BSc Information and Knowledge Systems (Software development) student. I major in Computer Science in my degree, and I have explored all sides of software engineering processes from first year till now. I have learnt a lot from this degree, and it has exposed me to systems analysis and in-depth web development, problem solving using data structures in (Java and C++) and systems development. I have experience with .NET technologies and have worked with C#. Currently I work with ionic,Python and Angular for my final year modules. |
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Our project aimed to contribute to GDPR compliance by designing a system that detects potential data violations in documents. We conducted extensive research on GDPR requirements using trusted resources like www.GDPR.eu , www.gdpr-info.eu and www.popiact-compliance.co.za. The system leverages natural language processing (NLP) and machine learning to scan documents for multiple categories of GDPR-protected data. It alerts users to potential violations, promoting compliance with European data protection regulations.
The project's research contribution lies in applying machine learning models to the specific context of GDPR. We explored AI frameworks to improve the accuracy of identifying sensitive information and developed a scalable, modular system architecture. Our research allowed us to narrow down the broadness of GDPR non-compliant data into categories that suited our project best. The categories we chose to identify are ones we believe to be the most common in text based documents.
Email: [email protected]
| Angular is used for building the frontend interface and handling client-side logic. | |
| Electron is used to package the Angular application into a desktop app. |
| Python is used for scripting and backend development. | |
| Flask is used to create RESTful APIs and manage backend logic. |
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PyTest is used for writing and running unit tests for the backend. |
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Karma is used as a test runner for Angular applications. |
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Jasmine is used for writing unit tests in JavaScript, commonly with Angular. |