Profile resolution across multilayer networks through smartphone camera fingerprint

In the last decade, various social platforms have been introduced on the web. Due to their specific orientation (friendship, professional connections, image sharing, etc.) users often join multiple networks. An important problem across these networks is the resolution of users profiles. That is, to identify if set of user profiles from different networks with different user ids or nicknames belong to the same user. The problem is more meaningful for resolving different profiles in digital forensic and criminal investigations. In this paper, we propose a method for profile resolution with the help of pictures being posted on different social platforms. We use the smartphone cameras which have become the source of instant image capturing and uploading process. In particular, we exploit the characteristic noise present in the images due to the manufacturing defects, to match user profiles across social platforms. To test our approach we select five different smartphones with two pairs of identical models, and three social platforms, namely Facebook, Google+ and WhatsApp. We evaluate our approach using real dataset of 1000 high-resolution pictures. The results indicate that even in the worst case our approach can provide profile matching upto 89.83%.