Most image forensics techniques rely on the analysis of traces left into the signal during the image acquisition process, which is supposed to be common among most devices. However, recent advances in visual technologies led several manufacturers to customize the acquisition pipeline in order to improve the image quality, by designing alternative coding schemes and in-camera processing. This fact threatens the effectiveness of available forensic techniques. It is thus required to study modern acquisition devices to both assess the effectiveness of available techniques and to develop new effective approaches. In this paper we focus on the source identification of images coming from one of the most spread moderm smartphones, i.e. the iPhone X. This model is significant since it comprises two main new features: the new HEIF compression standard, set as the default image format, and a brand new shooting mode, called Portrait Mode. We show that existing source identification methods are ineffective when images are acquired in Portrait Mode. We also show when and how it is possible to address this limitation by removing non unique artefacts introduced by the camera software.

Facing Image Source Attribution on iPhone X / Baracchi D.; Iuliani M.; Nencini A.G.; Piva A.. - ELETTRONICO. - 12617:(2021), pp. 196-207. (Intervento presentato al convegno 19th International Workshop on Digital Forensics and Watermarking, IWDW 2020 tenutosi a Australia nel November 25-27,) [10.1007/978-3-030-69449-4_15].

Facing Image Source Attribution on iPhone X

Baracchi D.;Iuliani M.;Piva A.
2021

Abstract

Most image forensics techniques rely on the analysis of traces left into the signal during the image acquisition process, which is supposed to be common among most devices. However, recent advances in visual technologies led several manufacturers to customize the acquisition pipeline in order to improve the image quality, by designing alternative coding schemes and in-camera processing. This fact threatens the effectiveness of available forensic techniques. It is thus required to study modern acquisition devices to both assess the effectiveness of available techniques and to develop new effective approaches. In this paper we focus on the source identification of images coming from one of the most spread moderm smartphones, i.e. the iPhone X. This model is significant since it comprises two main new features: the new HEIF compression standard, set as the default image format, and a brand new shooting mode, called Portrait Mode. We show that existing source identification methods are ineffective when images are acquired in Portrait Mode. We also show when and how it is possible to address this limitation by removing non unique artefacts introduced by the camera software.
2021
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
19th International Workshop on Digital Forensics and Watermarking, IWDW 2020
Australia
November 25-27,
Baracchi D.; Iuliani M.; Nencini A.G.; Piva A.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1231186
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? ND
social impact