Forensic Camera Identification in Social Networks via Camera Fingerprint

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Author(s): Tzuhuan Lin (New Taipei City Police Department, Taiwan)and Yu-Ru Wang (Yilan County Government Police Bureau, Taiwan)
Copyright: 2022
Pages: 13
Source title: Technologies to Advance Automation in Forensic Science and Criminal Investigation
Source Author(s)/Editor(s): Chung-Hao Chen (Old Dominion University, USA), Wen-Chao Yang (National Central Police University, Taiwan)and Lijia Chen (Henan University, China)
DOI: 10.4018/978-1-7998-8386-9.ch008

Keywords: Criminal Science and Forensics / Digital Crime & Forensics / Information Science Reference / Security & Forensics

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Abstract

Image-related crimes cause the urgent demand for tracing the origin of digital images. The breakthrough is a passive detection method via photo response non-uniformity (PRNU) analysis proposed by Lukáš et al. Recently, digital images are often shot with handheld devices (such as smartphones) and transmitted using social media (such as LINE). Most of the images are distorted (such as compressed and resized) during transmission. Previous studies are less focused on the impact of transmission compression through social networks. Thirty-one different Apple mobile phones were used to capture digital images in the experiment. Images were uploaded to the photo album via LINE software and then downloaded. The modified signed peak correlation energy (MSPCE) statistics is used to evaluate the correlation between the PRNU values of the disputed images and the pattern noise of the experimental devices. Experimental results show that the PRNU analysis method can effectively trace the source of the shot device using the distorted images which are compressed and resized during the transmission in LINE.

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Forensic Camera Identification in Social Networks via Camera Fingerprint

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