Too Much Information: Assessing Privacy Risks of Contact Trace Data Disclosure on People With COVID-19 in South Korea

Introduction: With the COVID-19 outbreak, South Korea has been making contact trace data public to help people self-check if they have been in contact with a person infected with the coronavirus. Despite its benefits in suppressing the spread of the virus, publicizing contact trace data raises concerns about individuals' privacy. In view of this tug-of-war between one's privacy and public safety, this work aims to deepen the understanding of privacy risks of contact trace data disclosure practices in South Korea. Method: In this study, publicly available contact trace data of 970 confirmed patients were collected from seven metropolitan cities in South Korea (20th Jan-20th Apr 2020). Then, an ordinal scale of relative privacy risk levels was introduced for evaluation, and the assessment was performed on the personal information included in the contact trace data, such as demographics, significant places, sensitive information, social relationships, and routine behaviors. In addition, variance of privacy risk levels was examined across regions and over time to check for differences in policy implementation. Results: It was found that most of the contact trace data showed the gender and age of the patients. In addition, it disclosed significant places (home/work) ranging across different levels of privacy risks in over 70% of the cases. Inference on sensitive information (hobby, religion) was made possible, and 48.7% of the cases exposed the patient's social relationships. In terms of regional differences, a considerable discrepancy was found in the privacy risk for each category. Despite the recent release of government guidelines on data disclosure, its effects were still limited to a few factors (e.g., workplaces, routine behaviors). Discussion: Privacy risk assessment showed evidence of superfluous information disclosure in the current practice. This study discusses the role of "identifiability" in contact tracing to provide new directions for minimizing disclosure of privacy infringing information. Analysis of real-world data can offer potential stakeholders, such as researchers, service developers, and government officials with practical protocols/guidelines in publicizing information of patients and design implications for future systems (e.g., automatic privacy sensitivity checking) to strike a balance between one's privacy and the public benefits with data disclosure.