Image Forensics has already achieved great results for the source camera identification task on images. Standard approaches for data coming from Social Network Platforms cannot be applied due to different processes involved (e.g., scaling, compression, etc.). In this paper, a classification engine for the reconstruction of the history of an image, is presented. Specifically, machine learning techniques and a-priori knowledge acquired through image analysis, we propose an automatic approach that can understand which Social Network Platform has processed an image and the software application used to perform the image upload. The engine makes use of proper alterations introduced by each platform as features. Results, in terms of global accuracy on a dataset of 2720 images, confirm the effectiveness of the proposed strategy.

A Classification Engine for Image Ballistics of Social Data

Giudice, Oliver;Moltisanti, Marco;Battiato, Sebastiano
2017-01-01

Abstract

Image Forensics has already achieved great results for the source camera identification task on images. Standard approaches for data coming from Social Network Platforms cannot be applied due to different processes involved (e.g., scaling, compression, etc.). In this paper, a classification engine for the reconstruction of the history of an image, is presented. Specifically, machine learning techniques and a-priori knowledge acquired through image analysis, we propose an automatic approach that can understand which Social Network Platform has processed an image and the software application used to perform the image upload. The engine makes use of proper alterations introduced by each platform as features. Results, in terms of global accuracy on a dataset of 2720 images, confirm the effectiveness of the proposed strategy.
2017
9783319685472
Digital ballistic; Image forensics; JPEG; Social networks; Theoretical Computer Science; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/335583
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