Interdependent privacy in third-party apps: past, present, and future

Gergely Biczok
Associate Professor
Budapest University of Technology and Economics

Abstract: In today’s networked online environments, privacy has become a complex affair. An important aspect of this complexity stems from the prominent interconnectedness of individuals, and therefore their personal data. Given this interconnectedness, an individual’s privacy is bound to be affected by the data sharing decisions of others, whether relatives, friends, or complete strangers. This scenario is exacerbated by the fact that certain types of information are inherently multi-subject in nature. The phenomenon emerging from such underlying factors is referred to as interdependent privacy (IDP), where personal information is shared by others, without the knowledge or direct consent of the data subject. In economic terms, this phenomenon can be attributed to an arising externality that influences the welfare of the data subject negatively without a compensation being offered. IDP is not just an academic curiosity; the Cambridge Analytica debacle convincingly demonstrated that it could have a real impact on our everyday lives. Accordingly, in this talk I offer a peak into IDP in third-party apps. Through our own work and others’, I will introduce the basic issue, the role of permissions, and potential mitigation methods; briefly touch upon how current data protection regulation deals with IDP; and also outline some ideas for the future.

Bio: Gergely is an associate professor in the CrySyS Lab and deputy head of department in the Dept. of Networked Systems and Services at the Budapest Univ. of Technology and Economics (BME), where he got his PhD in computer science in 2010. He held postdoctoral positions at the Norwegian Univ. of Science and Technolgy and the Hungarian Academy of Sciences, and was a research fellow at Ericsson Research. Gergely is a double Fulbrighter (Northwestern ’07-’08, Michigan ’24). His research and teaching have a focus on cybersecurity, data privacy, and the economics of networked systems. He is particular to the topic of interdependent privacy.