Title: On the usage of Sensor Pattern Noise for Picture-to-Identity linking through social network accounts
Authors: SATTA RICCARDOSTIRPARO PASQUALE
Citation: VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, Volume 3, Lisbon, Portugal, 5-8 January, 2014 vol. 3
Publisher: SCITEPRESS
Publication Year: 2014
JRC N°: JRC83665
ISBN: 978-989-758-009-3
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC83665
DOI: 10.5220/0004682200050011
Type: Articles in periodicals and books
Abstract: Digital imaging devices have gained an important role in everyone's life, due to a continuously decreasing price, and of the growing interest on photo sharing through social networks. As a result of the above facts, everyone continuously leaves visual 'traces' of her presence and life on the Internet, that can constitute precious data for forensic investigators. Digital Image Forensics is the task of analysing such digital images for collecting evidences. In this field, the recent introduction of techniques able to extract a unique 'fingerprint'' of the source camera of a picture, e.g. based on the Sensor Pattern Noise (SPN), has set the way for a series of useful tools for the forensic investigator. In this paper, we propose a novel usage of SPN, to find social network accounts belonging to a certain person of interest, who has shot a given photo. This task, that we name Picture-to-Identity linking, can be useful in a variety of forensic cases, e.g., finding stolen camera devices, cyber-bullying, or on-line child abuse. We experimentally test a method for Picture-to-Identity linking 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

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.