A PUF-based data-device hash for tampered image detection and source camera identification

With the increasing prevalent of digital devices and their abuse for digital content creation, forgeries of digital images and video footage are more rampant than ever. Digital forensics is challenged into seeking advanced technologies for forgery content detection and acquisition device identificat...

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Main Authors: Zheng, Yue, Cao, Yuan, Chang, Chip-Hong
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/137094
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1370942020-02-24T05:15:41Z A PUF-based data-device hash for tampered image detection and source camera identification Zheng, Yue Cao, Yuan Chang, Chip-Hong School of Electrical and Electronic Engineering Centre for Integrated Circuits and Systems Engineering::Electrical and electronic engineering Camera Identification Digital Image Forensics With the increasing prevalent of digital devices and their abuse for digital content creation, forgeries of digital images and video footage are more rampant than ever. Digital forensics is challenged into seeking advanced technologies for forgery content detection and acquisition device identification. Unfortunately, existing solutions that address image tampering problems fail to identify the device that produces the images or footage while techniques that can identify the camera is incapable of locating the tampered content of its captured images. In this paper, a new perceptual data-device hash is proposed to locate maliciously tampered image regions and identify the source camera of the received image data as a non-repudiable attestation in digital forensics. The presented image may have been either tampered or gone through benign content preserving geometric transforms or image processing operations. The proposed image hash is generated by projecting the invariant image features into a physical unclonable function (PUF)-defined Bernoulli random space. The tamper-resistant random PUF response is unique for each camera and can only be generated upon triggered by a challenge, which is provided by the image acquisition timestamp. The proposed hash is evaluated on the modified CASIA database and CMOS image sensor-based PUF simulated using 180 nm TSMC technology. It achieves a high tamper detection rate of 95.42% with the regions of tampered content successfully located, a good authentication performance of above 98.5% against standard content-preserving manipulations, and 96.25% and 90.42%, respectively, for the more challenging geometric transformations of rotation (0 ∼ 360◦) and scaling (scale factor in each dimension: 0.5). It is demonstrated to be able to identify the source camera with 100% accuracy and is secure against attacks on PUF. MOE (Min. of Education, S’pore) Accepted version 2020-02-24T05:15:41Z 2020-02-24T05:15:41Z 2019 Journal Article Zheng, Y., Cao, Y., & Chang, C.-H. (2019). A PUF-based data-device hash for tampered image detection and source camera identification. IEEE Transactions on Information Forensics and Security, 15620-634. 1556-6021 https://hdl.handle.net/10356/137094 10.1109/TIFS.2019.2926777 15 620 634 en IEEE Transactions on Information Forensics and Security © 2019 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. The published version is available at: https://doi.org/10.1109/TIFS.2019.2926777 application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Camera Identification
Digital Image Forensics
spellingShingle Engineering::Electrical and electronic engineering
Camera Identification
Digital Image Forensics
Zheng, Yue
Cao, Yuan
Chang, Chip-Hong
A PUF-based data-device hash for tampered image detection and source camera identification
description With the increasing prevalent of digital devices and their abuse for digital content creation, forgeries of digital images and video footage are more rampant than ever. Digital forensics is challenged into seeking advanced technologies for forgery content detection and acquisition device identification. Unfortunately, existing solutions that address image tampering problems fail to identify the device that produces the images or footage while techniques that can identify the camera is incapable of locating the tampered content of its captured images. In this paper, a new perceptual data-device hash is proposed to locate maliciously tampered image regions and identify the source camera of the received image data as a non-repudiable attestation in digital forensics. The presented image may have been either tampered or gone through benign content preserving geometric transforms or image processing operations. The proposed image hash is generated by projecting the invariant image features into a physical unclonable function (PUF)-defined Bernoulli random space. The tamper-resistant random PUF response is unique for each camera and can only be generated upon triggered by a challenge, which is provided by the image acquisition timestamp. The proposed hash is evaluated on the modified CASIA database and CMOS image sensor-based PUF simulated using 180 nm TSMC technology. It achieves a high tamper detection rate of 95.42% with the regions of tampered content successfully located, a good authentication performance of above 98.5% against standard content-preserving manipulations, and 96.25% and 90.42%, respectively, for the more challenging geometric transformations of rotation (0 ∼ 360◦) and scaling (scale factor in each dimension: 0.5). It is demonstrated to be able to identify the source camera with 100% accuracy and is secure against attacks on PUF.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zheng, Yue
Cao, Yuan
Chang, Chip-Hong
format Article
author Zheng, Yue
Cao, Yuan
Chang, Chip-Hong
author_sort Zheng, Yue
title A PUF-based data-device hash for tampered image detection and source camera identification
title_short A PUF-based data-device hash for tampered image detection and source camera identification
title_full A PUF-based data-device hash for tampered image detection and source camera identification
title_fullStr A PUF-based data-device hash for tampered image detection and source camera identification
title_full_unstemmed A PUF-based data-device hash for tampered image detection and source camera identification
title_sort puf-based data-device hash for tampered image detection and source camera identification
publishDate 2020
url https://hdl.handle.net/10356/137094
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