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|Title:||Picture-to-Identity linking of social network accounts based on Sensor Pattern Noise|
|Authors:||SATTA RICCARDO; STIRPARO PASQUALE|
|Citation:||5th International Conference on Imaging for Crime Detection and Prevention (ICDP 2013) p. 1.15|
|Publisher:||IET Digital Library|
|Type:||Articles in periodicals and books|
|Abstract:||The widespread diffusion of digital imaging devices fuelled a growing interest on photo sharing through social networks. Nowadays, Internet users continuously leave visual 'traces' of their presence and life on the Internet, which can constitute precious data for forensic investigators. Digital Image Forensics tools are used to analyse such images and collect evidences. One of such tools is the Sensor Pattern Noise (SPN), that is, an unique 'ﬁngerprint' left on a picture by the source camera sensor. In this paper, we propose and experimentally test a novel usage of SPN, to ﬁnd social network accounts belonging to a person of interest, who has shot a given photo. We name this task Picture-to-Identity linking, and believe it can be useful in a variety of forensic cases, e.g., ﬁnding stolen camera devices, cyber-bullying, or on-line child abuse. We evaluate two methods for Picture-to-Identity linking based on two existing SPN comparison techniques, on a benchmark data set of publicly accessible social network accounts collected from the Internet. The reported results are promising and show that such technique has a practical value for forensic practitioners.|
|JRC Directorate:||Space, Security and Migration|
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