Social network data analysis to highlight privacy threats in sharing data

AbstractSocial networks are a vast source of information, and they have been increasing impact on people's daily lives. They permit us to share emotions, passions, and interactions with other people around the world. While enabling people to exhibit their lives, social networks guarantee their privacy. The definitions of privacy requirements and default policies for safeguarding people's data are the most difficult challenges that social networks have to deal with. In this work, we have collected data concerning people who have different social network profiles, aiming to analyse privacy requirements offered by social networks. In particular, we have built a tool exploiting image-recognition techniques to recognise a user from his/her picture, aiming to collect his/her personal data accessible through social networks where s/he has a profile. We have composed a dataset of 5000 users by combining data available from several social networks; we compared social network data mandatory in the registration phases, publicly accessible and those retrieved by our analysis. We aim to analyse the amount of extrapolated data for evaluating privacy threats when users share information on different social networks to help them be aware of these aspects. This work shows how users data on social networks can be retrieved easily by representing a clear privacy violation. Our research aims to improve the user's awareness concerning the spreading and managing of social networks data. To this end, we highlighted all the statistical evaluations made over the gathered data for putting in evidence the privacy issues

CHRAVAT - Chronology Awareness Visual Analytic Tool

Nowadays, the amount of information spread over networks is extremely large, and many sensible data are granted by legitimate owners aiming to exploit different networking services. In particular, the majority of people give their own consent for processing personal data without understanding how network providers will manage them, and if they will be shared among different network providers. In this paper, we propose a tool exploiting visualization techniques in order to make a user aware of how his/her personal data are exchanged and shared during daily web browsing activities. In particular, the proposed tool enables a user to interactively visualize the communication flows during the aforesaid browsing process, and to discover possibly hidden network providers involved in it. Moreover, the graphical interface also provides real-time summary graphs, which show the amount of information acquired from the network. Finally, we performed several users studies aiming to analyse how the tool can improve the user's perception on the privacy issues that s/he is exposed to. Results demonstrate the effectiveness of the proposed tool