Project A2

Privacy Implications of Visual
Data Dissemination

Principal Investigators

Mario Fritz

Project Summary

Many people share and disseminate massive amounts of visual data (images, videos), be it on webpages, in social networks or through personal communication. Even though it is obvious that visual data contains privacy relevant information, it is unclear, which privacy implications visual data dissemination has for individuals sharing such information and for others that can be associated to the visual information.
This project has investigated methods that extract such privacy relevant information from visual data in order to get a better understanding of the implications of releasing visual data. The investigations are structured into four parts. The first focus is on what type of information can be extracted from such data sources in terms of activities, interactions and social roles. Second, linkability of persons between different data recordings was investigated in order to understand how the aggregation of large sources of visual data will affect privacy. Third, connections to social network were established in order to understand the different quality and complementarity of information that can extracted from visual sources.
Fourth, we model the implication of releasing additional visual data under different attack scenarios and counter measures in order to evaluate different options users might consider. Throughout the project, we are tightly interlinked with other CRC projects by providing the results of our visual analysis in order to arrive at a more holistic picture of data emitted by users in the context of social networks, and evaluating different threat scenarios for the user. We approached the associated challenges by researching computer vision and probabilistic inference methods to extract and infer privacy relevant information from disseminated visual data. Also, possible counter measures were explored such as blurring of faces of individuals and how much (or little) effect this had on the information that can be inferred.

Role Within the Collaborative Research Center