IMGCAT: An approach to dismantle the anonymity of a source camera using correlative features and an integrated 1D convolutional neural network

Muhammad Irshad; Ngai-Fong Law; K.H. Loo; Sami Haider

doi:10.1016/j.array.2023.100279

journal article Open Access Jul 01, 2023

IMGCAT: An approach to dismantle the anonymity of a source camera using correlative features and an integrated 1D convolutional neural network

Muhammad Irshad

Ngai-Fong Law K.H. Loo Sami Haider

Array Vol. 18 pp. 100279 · Elsevier BV

View at Publisher Save 10.1016/j.array.2023.100279

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References

50

[1]

Dimitriadis "D4I - digital forensics framework for reviewing and investigating cyber attacks" Array (2020) 10.1016/j.array.2019.100015

[2]

Liu "Efficient source camera identification with diversity-enhanced patch selection and deep residual prediction" Sensors (2021) 10.3390/s21144701

[3]

Irshad "City vision: CCTV images based public surveillance model" (2021)

[4]

Law "PRNU-based source identification for network video surveillance system" (2018)

[5]

Nowroozi "A survey of machine learning techniques in adversarial image forensics" Comput Secur (2021) 10.1016/j.cose.2020.102092

[6]

Bhima Koregaon case: Forensics report states evidence was planted in case against Indian activists accused of plotting to overthrow the Modi government - the Washington Post.” https://www.washingtonpost.com/world/asia_pacific/india-bhima-koregaon-activists-jailed/2021/02/10/8087f172-61e0-11eb-a177-7765f29a9524_story.html (accessed Jan. 27, 2022).

[7]

Avidan "Seam carving for content-aware image resizing" Proc ACM SIGGRAPH Conf Comput Graph (2007)

[8]

Nam "Deep convolutional neural network for identifying seam-carving forgery" IEEE Trans Circ Syst Video Technol (2021) 10.1109/tcsvt.2020.3037662

[9]

Dirik "Analysis of seam-carving-based anonymization of images against PRNU noise pattern-based source attribution" IEEE Trans Inf Forensics Secur (2014) 10.1109/tifs.2014.2361200

[10]

Shi "A local variance based approach to alleviate the scene content interference for source camera identification" Digit Invest (2017) 10.1016/j.diin.2017.07.005

[11]

Chai "SQL: superpixels via quaternary labeling" Pattern Recogn (2019) 10.1016/j.patcog.2019.03.012

[12]

RubinsteinMichael "Improved seam carving for video retargeting" ACM Trans Graph (2008)

[13]

Shamir "Seam carving for media retargeting" Commun ACM (2009) 10.1145/1435417.1435437

[14]

Frankovich "Enhanced seam carving via integration of energy gradient functionals" IEEE Signal Process Lett (2011) 10.1109/lsp.2011.2140396

[15]

Popescu "Exposing digital forgeries by detecting traces of resampling" IEEE Trans Signal Process (2005) 10.1109/tsp.2004.839932

[16]

Han "Exploring the location of object deleted by seam-carving" Expert Syst Appl (2018) 10.1016/j.eswa.2017.11.023

[17]

Ryu "Detecting trace of seam carving for forensic analysis" IEICE Trans Info Syst (2014) 10.1587/transinf.e97.d.1304

[18]

Rashid "Image denoising using wavelet transform" Front Artif Intell Appl (2019)

[19]

Zhou "A review: deep learning for medical image segmentation using multi-modality fusion" Array (2019) 10.1016/j.array.2019.100004

[20]

Yoon "Frame-rate up-conversion detection based on convolutional neural network for learning spatiotemporal features" Forensic Sci Int (2022) 10.1016/j.forsciint.2022.111442

[21]

Rai "Visual attention, visual salience, and perceived interest in multimedia applications" Acad Press Libr Signal Process Image Video Process Anal Comput Vis (2018)

[22]

Sarkar "Detection of seam carving and localization of seam insertions in digital images" (2009)

[23]

Da Wei "A patch analysis method to detect seam carved images" Pattern Recogn Lett (2014) 10.1016/j.patrec.2013.09.026

[24]

Chan "A two dimensional camera identification method based on image sensor noise" ICASSP, IEEE Int Conf Acoust Speech Signal Process - Proc (2012)

[25]

Boroumand "Deep residual network for steganalysis of digital images" IEEE Trans Inf Forensics Secur (2019) 10.1109/tifs.2018.2871749

[26]

Zhang "An improved sensor pattern noise estimation method based on edge guided weighted averaging" Lect Notes Comput Sci (2020) 10.1007/978-3-030-62460-6_36

[27]

Garg (2022)

[28]

Bayar "Constrained convolutional neural networks: a new approach towards general purpose image manipulation detection" IEEE Trans Inf Forensics Secur (2018) 10.1109/tifs.2018.2825953

[29]

Nam "Two-stream network for detecting double compression of H.264 videos" Proc - Int Conf Image Process ICIP (2019)

[30]

Simonyan "Very deep convolutional networks for large-scale image recognition" (2015)

[31]

ImageNet Large Scale Visual Recognition Challenge

Olga Russakovsky, Jia Deng, Hao Su et al.

International Journal of Computer Vision 2015 10.1007/s11263-015-0816-y

[32]

Ye "A convolutional neural network based seam carving detection scheme for uncompressed digital images" Lect Notes Comput Sci (2019) 10.1007/978-3-030-11389-6_1

[33]

Lukáš "Digital camera identification from sensor pattern noise" IEEE Trans Inf Forensics Secur (2006) 10.1109/tifs.2006.873602

[34]

Bayram "Seam-carving based anonymization against image & video source attribution" (2013)

[35]

Taspinar "PRNU-based camera attribution from multiple seam-carved images" IEEE Trans Inf Forensics Secur (2017) 10.1109/tifs.2017.2737961

[36]

Li "Structure-aware image fusion" Optik (2018) 10.1016/j.ijleo.2018.06.123

[37]

Ssengonzi "A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization" Array (2022) 10.1016/j.array.2022.100142

[38]

Irshad "CamCarv - Expose the Source Camera at the Rear of Seam Insertion" (2023)

[39]

Baldini "A survey of techniques for the identification of mobile phones using the physical fingerprints of the built-in components" IEEE Commun. Surv. Tutorials (2017) 10.1109/comst.2017.2694487

[40]

Deep learning in neural networks: An overview

Jürgen Schmidhuber

Neural Networks 2015 10.1016/j.neunet.2014.09.003

[41]

Gloe "The ‘dresden image database’ for benchmarking digital image forensics" (2010)

[42]

Shullani "VISION: a video and image dataset for source identification" EURASIP J Inf Secur (2017)

[43]

Ma "SITUP: scale invariant tracking using average peak-to-correlation energy" IEEE Trans Image Process (2020) 10.1109/tip.2019.2962694

[44]

Iqbal "Seam carve detection using convolutional neural networks" Lect Notes Inst Comput Sci Soc Telecommun Eng LNICST (2019)

[45]

Cieslak "Seam carving detection using convolutional neural networks" (2018)

[46]

Ahmadi "Context-aware saliency detection for image retargeting using convolutional neural networks" Multimed Tool Appl (2021) 10.1007/s11042-020-10185-0

[47]

Karaküҫük "Recent advances in counter PRNU based source attribution and beyond" Media Watermark Secur Foren (2015)

[48]

Costa "Open set source camera attribution and device linking" Pattern Recogn Lett (2014) 10.1016/j.patrec.2013.09.006

[49]

Zhao "Source camera identification via low dimensional PRNU features" Multimed Tool Appl (2018) 10.1007/s11042-018-6809-4

[50]

Jahanirad "An evolution of image source camera attribution approaches" Forensic Sci Int (2016) 10.1016/j.forsciint.2016.03.035

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Details

Published: Jul 01, 2023
Vol/Issue: 18
Pages: 100279
License: View

Authors

Funding

Hong Kong Polytechnic University

Cite This Article

Muhammad Irshad, Ngai-Fong Law, K.H. Loo, et al. (2023). IMGCAT: An approach to dismantle the anonymity of a source camera using correlative features and an integrated 1D convolutional neural network. Array, 18, 100279. https://doi.org/10.1016/j.array.2023.100279

IMGCAT: An approach to dismantle the anonymity of a source camera using correlative features and an integrated 1D convolutional neural network

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