Analysis of Data’s Privacy and Anonymity Aspects of Contact Tracing Apps via Smartphones – A Use Case of COVID-19 - Akkineni, Haritha; Myneni, Madhu Bala; Padmaja, Budi; Ravuri, Ananda; Moorthy, CH. V. K. N. S. N.; CMS, Raviteja (Journal of Mobile Multimedia, 2023)
Privacy and anonymity aspects are playing a vital role in accessing smartphone apps. This is more evident in unexpected epidemic situations like COVID-19 while working with contact tracing apps. A human connectivity model is essential to analyse the widespread cases of viruses and vaccination patterns during the timeframe of March 2020 to May 2021. Smartphone apps that are supported by technologies like IoT and blockchain have already proven effective in tracing the Ebola epidemic. Thus, this technology, coupled with privacy-preserving features, would help to discover clusters with infectious contacts and alert the respective authorities. Besides, this can also allow us to understand the human connectivity model and the effectiveness of vaccines, which can aid in developing a plan of action for future epidemics. Hence, this article focuses on the analysis of data collected from contact tracing apps and a number of affected cases. It includes a study on early solutions with existing technologies, an overview and analysis of existing COVID-19 apps with vulnerabilities, proposed solutions, and data analysis on privacy and anonymity aspects of smartphone apps using the ARIMA model. It is evaluated by correlating it with the usage of contact tracing apps. The results assured a positive correlation between the number of downloads and the number of cases. This infers that even though the Indian government released these contact tracing apps, it all depends on the citizens to utilise them to their fullest. As a policy suggestion, it is stated that regardless of the prevalence of contact tracing apps, people must follow the rules and regulations suggested by the local health authorities and maintain social distancing in public places.