Escaping the Big Brother: An empirical study on factors influencing identification and information leakage on the Web

Abstract

This paper presents a study on factors that may increase the risks of personal information leakage, owing to the possibility of connecting user profiles that are not explicitly linked together. First, we introduce a technique for user identification based on cross-site checking and linking of user attributes. Then, we describe the experimental evaluation of the identification technique both in a real setting and on an online sample, showing its accuracy to discover unknown personal data. Finally, we combine the results on the accuracy of identification with the results of a questionnaire completed by the same subjects who performed the test in the real setting. The aim of the study was to discover possible factors that make users vulnerable to this kind of technique. We found that the number of social networks used, their features and especially the amount of profiles abandoned and forgotten by the user are factors that increase the likelihood of identification and the privacy risks.