For my dissertation thesis I chose to implement a Coronavirus statistics app for Romania using differential privacy. Differential privacy is a concept in data privacy that aims to protect the privacy of individuals while allowing access to their data for statistical analysis. It provides a mathematical framework for measuring the privacy guarantees of a data analysis algorithm, and ensures that the algorithm does not reveal any individual's sensitive information.
The basic idea behind differential privacy is to add a controlled amount of random noise to a dataset, in order to hide the information of any specific individual. This noise is added in a way that is calibrated to the sensitivity of the data, so that the privacy of individuals is protected while still preserving the overall statistical properties of the dataset.
My inspiration for the project is the Australia Covid-19 Real-time Information System for Preparedness and Epidemic Response.Technologies used for the project are React with Javascript on frontend and Spring Boot on backend.
The starting page contains the authentication,where the user logins with the credentials or creates a new account.
If the user doesn’t have an account,they can sign up and register.For registration I used react hook form to validate data on front end and put a min limit of 4 letters and max limit of 20 for password,age greater than 18.
On the main page I created a menu,which contains the home page,links to the data science and sites of infection,alert message system and about us page.
Contact page,where the user can get in touch with someone through the website.The form contains input for name,email adress and message.
For exposure sites I plan to display deaths for each county, along with a map with statistics and a graph with active covid, recovered and deaths.
