The Library
PRNU-based image classification of origin social network with CNN
Tools
Caldelli, Roberto, Amerini, Irene and Li, Chang-Tsun (2018) PRNU-based image classification of origin social network with CNN. In: 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, 3-7 Aug 2018 ISBN 9789082797015. doi:10.23919/EUSIPCO.2018.8553160 ISSN 2076-1465.
|
PDF
WRAP-PRNU-based-image-classification-origin-social-network-CNN-Li-2018.pdf - Accepted Version - Requires a PDF viewer. Download (3084Kb) | Preview |
Official URL: https://doi.org/10.23919/EUSIPCO.2018.8553160
Abstract
A huge amount of images are continuously shared on social networks (SNs) daily and, in most of cases, it is very difficult to reliably establish the SN of provenance of an image when it is recovered from a hard disk, a SD card or a smartphone memory. During an investigation, it could be crucial to be able to distinguish images coming directly from a photo-camera with respect to those downloaded from a social network and possibly, in this last circumstance, determining which is the SN among a defined group. It is well known that each SN leaves peculiar traces on each content during the upload-download process; such traces can be exploited to make image classification. In this work, the idea is to use the PRNU, embedded in every acquired images, as the “carrier” of the particular SN traces which diversely modulate the PRNU. We demonstrate, in this paper, that SN-modulated noise residual can be adopted as a feature to detect the social network of origin by means of a trained convolutional neural network (CNN).
Item Type: | Conference Item (Paper) | ||||||
---|---|---|---|---|---|---|---|
Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
Library of Congress Subject Headings (LCSH): | Social networks, Digital cameras -- Identification, Neural networks (Computer science), Smartphones, Online social networks -- Computer networks -- Security measures, Data encryption (Computer science), Digital images -- Watermarking | ||||||
Publisher: | IEEE | ||||||
ISBN: | 9789082797015 | ||||||
ISSN: | 2076-1465 | ||||||
Official Date: | 3 December 2018 | ||||||
Dates: |
|
||||||
DOI: | 10.23919/EUSIPCO.2018.8553160 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Reuse Statement (publisher, data, author rights): | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 18 May 2020 | ||||||
Date of first compliant Open Access: | 18 May 2020 | ||||||
RIOXX Funder/Project Grant: |
|
||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | 26th European Signal Processing Conference (EUSIPCO) | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Rome, Italy | ||||||
Date(s) of Event: | 3-7 Aug 2018 |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year