Studying the impact of sharing platforms like social networks and messaging services on multimedia content nowadays represents a due step in multimedia forensics research. In this framework, we study the characteristics of images that are uploaded and shared through three popular mobile messaging apps combined with two different sending mobile operating systems (OS). In our analysis, we consider information contained both in the image signal and in the metadata of the image file. We show that it is generally possible to identify a posteriori the last app and the OS that have been used for uploading. This is done by considering different scenarios involving images shared both once and twice. Moreover, we show that, by leveraging the knowledge of the last sharing app and system, it is possible to retrieve information on the previous sharing step for double shared images. In relation to prior works, a discussion on the influence of the rescaling and recompression mechanism - usually performed differently through apps and OSs - is also proposed, and the feasibility of retrieving the compression parameters of the image before being shared is assessed.

Identifying image provenance: An analysis of mobile instant messaging apps / Phan, Quoc-Tin; Pasquini, Cecilia; Boato, Giulia; De Natale, Francesco G. B.. - (2018), pp. 1-6. (Intervento presentato al convegno MMSP 2018 tenutosi a Vancouver nel 29th-31st August 2018) [10.1109/MMSP.2018.8547050].

Identifying image provenance: An analysis of mobile instant messaging apps

Phan, Quoc-Tin;Pasquini, Cecilia;Boato, Giulia;De Natale, Francesco G. B.
2018-01-01

Abstract

Studying the impact of sharing platforms like social networks and messaging services on multimedia content nowadays represents a due step in multimedia forensics research. In this framework, we study the characteristics of images that are uploaded and shared through three popular mobile messaging apps combined with two different sending mobile operating systems (OS). In our analysis, we consider information contained both in the image signal and in the metadata of the image file. We show that it is generally possible to identify a posteriori the last app and the OS that have been used for uploading. This is done by considering different scenarios involving images shared both once and twice. Moreover, we show that, by leveraging the knowledge of the last sharing app and system, it is possible to retrieve information on the previous sharing step for double shared images. In relation to prior works, a discussion on the influence of the rescaling and recompression mechanism - usually performed differently through apps and OSs - is also proposed, and the feasibility of retrieving the compression parameters of the image before being shared is assessed.
2018
2018 IEEE 20th International Workshop on Multimedia Signal Processing, MMSP 2018
Piscataway, NJ
Institute of Electrical and Electronics Engineers Inc.
9781538660706
Phan, Quoc-Tin; Pasquini, Cecilia; Boato, Giulia; De Natale, Francesco G. B.
Identifying image provenance: An analysis of mobile instant messaging apps / Phan, Quoc-Tin; Pasquini, Cecilia; Boato, Giulia; De Natale, Francesco G. B.. - (2018), pp. 1-6. (Intervento presentato al convegno MMSP 2018 tenutosi a Vancouver nel 29th-31st August 2018) [10.1109/MMSP.2018.8547050].
File in questo prodotto:
File Dimensione Formato  
MMSP2018_submission.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 521.85 kB
Formato Adobe PDF
521.85 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/225914
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 16
  • ???jsp.display-item.citation.isi??? ND
social impact